Scientific and technological development stage identification and prediction method based on life cycle matrix

Abstract

The invention relates to a science and technology development stage identification and prediction method based on a life cycle matrix. The method comprises the steps of determining a direction involved in the science and technology field; scientific and technological papers and patent literatures are retrieved, time sequence data of the publication quantity of the scientific and technological papers and the application quantity of patents are obtained, S curve fitting is carried out, and time nodes of the scientific and technological field in the germination stage, the growth stage, the mature stage and the decline stage of basic research and technology application are identified; taking the basic research stage and the technical application stage as horizontal and vertical coordinates, and constructing a life cycle matrix according to a time overlapping region division result of the basic research stage and the technical application stage; and according to the life cycle matrix and the duration of each stage, an evolution trend curve of the fundamental research and technology application stage is drawn, and field growth pattern recognition and development law prediction are carried out. According to the method, the interaction relationship between the basic research and the technical application in the scientific and technological development process is demonstrated, and guidance is provided for identifying and predicting the scientific and technological development stage and trend.

Description

Technical Field

[0001] The present invention belongs to the technical field of literature data analysis and processing, and relates to a method for identifying and predicting the development stage of science and technology based on a life cycle matrix. Background Art

[0002] As the core driving force for social development, the research on the development stage of science and technology has important theoretical value and practical significance. The academic community has successively proposed theoretical frameworks such as the linear model and the Pasteur quadrant model, systematically explaining the evolution characteristics of science and technology in basic research, applied research, technological innovation, industrial application and other links. To deeply reveal the process of technology evolution and improve the technology prediction ability, the technology life cycle theory came into being. This theory divides the development process of technology into four stages: germination period, growth period, maturity period and decline period, providing an important theoretical support for the identification and prediction of the technology development track. On this basis, analysis methods such as the technology maturity method, the S-curve method, the technology life cycle graph method, and the patent index analysis method have emerged continuously, further enriching and perfecting the theoretical system and methodological basis of technology development research.

[0003] Zhang Huiqin et al.

Zhang Huiqin, Wang Xin, Wang Xu, et al. Dynamic Evolution Model of Basic Research Beyond the Pasteur Quadrant and Its Practical Connotation [J]. Engineering Sciences in China, 2021, 23(04): 145-152.

[0004] However, the existing theoretical models still have limitations in explaining the development stage and law of science and technology. On the one hand, traditional theoretical frameworks such as the linear model and the Pasteur quadrant model are more suitable for retrospective analysis and law summary of relatively mature scientific and technological fields, and it is difficult to identify and predict the current and future development stages of emerging scientific and technological fields. On the other hand, although the technology life cycle theory provides an analysis tool for identifying and predicting the technology development stage, its main focus is on the technology application level, and it fails to fully reflect the role of basic research in the development of science and technology, nor can it reveal the complex interaction mechanism and co-evolution relationship between basic research and applied research. Therefore, on the basis of the technology life cycle theory, it is necessary to further highlight the stage characteristics and role of basic research in the process of field development to more comprehensively present the stage characteristics and internal laws of science and technology development. Summary of the Invention

[0005] The technical problem solved by the present invention is: to overcome the deficiencies of the prior art, and propose a method for identifying and predicting the development stages of science and technology based on the life cycle matrix, further highlighting the stage characteristics and roles of basic research in the process of field development, so as to more comprehensively present the stage characteristics and internal laws of the development of science and technology, identify and predict emerging fields with great development potential and large research space for researchers, and identify high-value fields with mature and stable technology applications and basic research, low risks for enterprise investment and profit.

[0006] The solution to the technical problem of the present invention is: In the first aspect, a method for identifying and predicting the development stages of science and technology based on the life cycle matrix is proposed, including the following steps:

[0007] Determine the science and technology field, clarify the directions involved in the science and technology field, and define the specific scope with keywords;

[0008] Determine the scientific paper retrieval formula and the patent retrieval formula, select a database to retrieve scientific papers and patent documents, and obtain the time series data of the scientific paper publication volume and the patent application volume;

[0009] Perform S-curve fitting on the time series data of the scientific paper publication volume and the patent application volume respectively to identify the time nodes of each development stage of the science and technology field in the germination period, growth period, maturity period, and decline period of basic research and technology application; among them, the S-curve fitting result of the time series data of the scientific paper publication volume corresponds to basic research, and the S-curve fitting result of the time series data of the patent application volume corresponds to technology application;

[0010] Take the basic research development stage and the technology application development stage as the horizontal and vertical coordinates, and construct a life cycle matrix according to the division result of the time coincidence area of the basic research development stage and the technology application development stage;

[0011] According to the constructed life cycle matrix and the duration of each development stage, draw the evolution trend curves of the basic research and technology application stages;

[0012] According to the evolution trend curves of the basic research and technology application stages, combined with the existing development evidence related to the field, identify the field growth mode and predict the development law.

[0013] Furthermore, the time series data of the scientific paper publication volume and the patent application volume represent the number of scientific papers and patent applications retrieved in each time period. It is possible to select one year as a time period, or select a time period of 2 to 3 years.

[0014] Further, the time series data of the number of scientific and technological papers published and the number of patent applications are respectively subjected to S-curve fitting to identify the time nodes of each development stage of the scientific and technological field in the germination period, growth period, maturity period, and decline period of basic research and technological applications, including:

[0015] According to the time series data of the number of scientific and technological papers published and the number of patent applications, the cumulative annual values of the number of scientific and technological papers and the cumulative annual values of the number of patent applications are calculated. Taking the cumulative annual values of the number of scientific and technological papers and the cumulative annual values of the number of patent applications as inputs respectively, S-curve fitting is carried out according to formula (1) to obtain the fitting curves of time and the number of scientific and technological papers, and the fitting curves of time and the number of patent applications, and the fitting parameter values are obtained, including the saturation value, inflection point, growth time, and determination coefficient R 2 , where R 2 is used to determine the fitting effect of the S-curve;

[0016]

[0017] Among them, K represents the saturation value, which is the limit value of the cumulative effect. During the entire life cycle, the cumulative value will infinitely approach the saturation value; t m represents the inflection point, which is the demarcation point between the growth period and the maturity period. At this point, the curve growth rate reaches the maximum value. Before this point, the growth rate continuously increases, and after this point, the growth rate gradually decreases; Δt represents the growth time, which is the time experienced by the cumulative effect from 10% of the saturation value to 90% of the saturation value, spanning the entire growth period and maturity period;

[0018] According to the S-curve, identify the critical values for the division of the life cycle stages: Let t x be the time node when the cumulative effect reaches x% of the saturation value. Then, before t 10 is the germination period, between t 10 and t m is the growth period, between t m and t 90 is the maturity period, and after t 90 is the decline period.

[0019] Further, the construction of the life cycle matrix includes:

[0020] Use the letter b to represent basic research, the letter a to represent technological application, and use the numbers [1, 2, 3, 4] to represent the four stages of the germination period, growth period, maturity period, and decline period respectively, to obtain the values of the array (b, a) in different stages, and a total of 16 groups of coordinate points are formed;

[0021] Taking t 10 , t m , t 90As a dividing node, draw the time axis of the basic research development stage and the time axis of the technology application development stage, divide the time overlapping area of the basic research development stage and the technology application development stage, obtain all the combined situations of the development stages of basic research b and technology application a, and then obtain all the (b, a) coordinate points occupied by this scientific and technological field, and construct a life cycle matrix.

[0022] Furthermore, according to the values of the array (b, a) in different stages, it is divided into four regions:

[0023] (1, 1), (1, 2), (2, 1), (2, 2) The enclosed area, whether it is basic research or technology application, is in the budding and growing stage. It is considered that this scientific and technological field is an emerging field with great development potential; (3, 1), (3, 2), (4, 1), (4, 2) The enclosed area, the basic research has matured but the technology application is still in the budding and developing stage. It is considered that this scientific and technological field is a field with application value but has not yet been realized, or belongs to a more pure theoretical research field with unclear application value; (1, 3), (1, 4), (2, 3), (2, 4) The enclosed area, the technology application has entered the mature stage, and the basic research is still in the budding and growing stage, indicating that the technology application of this scientific and technological field has preceded the basic research, and the further development of the field requires new theories and breakthroughs in basic research; (3, 3), (3, 4), (4, 3), (4, 4) The enclosed area, both the technology application and the basic research have developed and matured. In the future, the breakthrough and development of this scientific and technological field will more need new breakthroughs in other fields to activate.

[0024] Furthermore, the drawing of the evolution trend curves of the basic research and technology application stages includes:

[0025] Based on the constructed life cycle matrix, calculate the durations of the budding, growing, mature, and declining periods of the scientific and technological field in basic research and technology application respectively;

[0026] Combine the basic research development stage b, the technology application development stage a, and the duration t of a certain stage to form a three-dimensional array (b, a, t), obtain the development law coordinate sequence, and visualize the coordinate sequence to obtain the evolution trend curves of the basic research and technology application stages.

[0027] Furthermore, the identification of the field growth mode and the prediction of the development law include:

[0028] Identify the historical development stage, identify the current development stage and the duration of the current stage, and predict when it will enter what future development stage.

[0029] In a second aspect, a computer-readable storage medium is provided. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method for identifying and predicting the technological development stage based on the life cycle matrix are implemented.

[0030] In a third aspect, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the method for identifying and predicting the technological development stage based on the life cycle matrix are implemented.

[0031] In a fourth aspect, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the steps of the method for identifying and predicting the technological development stage based on the life cycle matrix are implemented.

[0032] The beneficial effects of the present invention compared with the prior art are as follows:

[0033] (1) Through the life cycle matrix method, the present invention realizes the refined division, identification, and prediction of the development stage of the technology field. Compared with the technology life cycle method in the prior art, it can reflect the stage characteristics of basic research in the development process of the technology field.

[0034] (2) The curve graph of the technological development stage and future evolution trend of the present invention realizes the quantitative description and visual presentation of the evolution law of the technology field at different development stages, and predicts the duration at different stages. Description of the Drawings

[0035] Figure 1 is the flow chart of the method for identifying and predicting the technological development stage based on the life cycle matrix provided by the present invention;

[0036] Figure 2 is the life cycle matrix model diagram of the method for identifying and predicting the technological development stage based on the life cycle matrix provided in Embodiment 1 of the present invention;

[0037] Figure 3 is the S-curve fitting diagram of scientific papers of the method for identifying and predicting the technological development stage based on the life cycle matrix provided in Embodiment 1 of the present invention;

[0038] Figure 4 is the S-curve fitting diagram of patent data of the method for identifying and predicting the technological development stage based on the life cycle matrix provided in Embodiment 1 of the present invention;

[0039] Figure 5 is the life cycle matrix diagram of the brain-computer interface field of the method for identifying and predicting the technological development stage based on the life cycle matrix provided in Embodiment 1 of the present invention;

[0040] Figure 6 It is a curve graph of the technological development stage and future evolution trend of a method for identifying and predicting the technological development stage based on the life cycle matrix provided in Embodiment 1 of the present invention;

[0041] Figure 7 It is an S-curve fitting graph of scientific papers of a method for identifying and predicting the technological development stage based on the life cycle matrix provided in Embodiment 2 of the present invention;

[0042] Figure 8 It is an S-curve fitting graph of patent data of a method for identifying and predicting the technological development stage based on the life cycle matrix provided in Embodiment 2 of the present invention;

[0043] Figure 9 It is a life cycle matrix diagram of the brain-computer interface field of a method for identifying and predicting the technological development stage based on the life cycle matrix provided in Embodiment 2 of the present invention. Detailed implementation manners

[0044] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0045] As Figure 1 shown, a method for identifying and predicting the technological development stage based on the life cycle matrix proposed by the present invention includes the following steps:

[0046] S1: Determine the technological field, clarify the directions involved in the technological field, and define the specific scope with keywords;

[0047] S2: Determine the scientific paper retrieval formula and the patent retrieval formula, select a database to retrieve scientific papers and patent documents, and obtain the time series data of the scientific paper publication volume and the patent application volume;

[0048] Among them, the time series data of the scientific paper publication volume and the patent application volume represents the number of scientific papers and patent applications retrieved in each time period. It can be selected with 1 year as a time period, or it can be selected with 2 - 3 years as a time period.

[0049] S3: Perform S-curve fitting on the time series data of the scientific paper publication volume and the patent application volume respectively to identify the time nodes of each development stage of the technological field in the germination period, growth period, maturity period, and decline period of basic research and technological application; among them, the S-curve fitting result of the time series data of the scientific paper publication volume corresponds to basic research, and the S-curve fitting result of the time series data of the patent application volume corresponds to technological application;

[0050] S4: Take the basic research development stage and the technology application development stage as the horizontal and vertical coordinates, and construct a life cycle matrix according to the division results of the time overlap area between the basic research development stage and the technology application development stage;

[0051] S5: Draw the evolution trend curves of the basic research and technology application stages according to the constructed life cycle matrix and the duration of each development stage;

[0052] S6: Identify the field growth mode and predict the development law according to the evolution trend curves of the basic research and technology application stages, combined with the existing development evidence in the field.

[0053] Example 1

[0054] This example takes the field of brain-computer interface as an example and provides an identification and prediction result of the development stage of the technology field. As Figure 1 shown, the method of Example 1 includes the following steps:

[0055] S101: Determine the technology field, clarify the directions involved in the technology field, and define the specific scope with keywords.

[0056] In this example, the brain-computer interface is selected as the research field, and academic journals, conference proceedings, and authoritative research reports in the technology field are consulted; the technology field is comprehensively sorted out to clarify the main directions and sub-fields covered by the technology field, and the research scope is accurately defined in the form of keywords.

[0057] S102: Determine the scientific paper retrieval formula and the patent retrieval formula, select a database to retrieve scientific papers and patent documents, and obtain the time series data of the scientific paper publication volume and the patent application volume;

[0058] According to the determined keywords, after multiple rounds of retrieval attempts, the scientific paper retrieval formula and the patent retrieval formula in the field of brain-computer interface are finally formed as TS = ("brain-computer interfac*" OR "brain-computer communicat*" OR "brain-machine communicat*" OR "brain-machine interfac*" OR "direct braininterfac*" OR "direct neural interfac*" OR "mind machine interfac*" OR "neuralcontrol interfac*" OR “brain-to-brain”); the data source of scientific papers is selected as the Web of Science database, and the data source of patent applications is selected as the Derwent Innovations Index database.

[0059] Input the search formula into the selected databases respectively, and screen the date range and document types through the advanced search function; obtain the cumulative values of the number of scientific papers and the cumulative values of the number of patent applications year by year according to the search results respectively.

[0060] S103: Perform S-curve fitting on the time series data of the number of scientific papers published and the number of patent applications respectively, and identify the time nodes of the germination period, growth period, maturity period, and decline period of basic research and technological applications in the scientific and technological fields respectively; among them, the S-curve fitting result of the time series data of the number of scientific papers published corresponds to basic research, and the S-curve fitting result of the time series data of the number of patent applications corresponds to technological applications.

[0061] According to the time series data of the number of scientific papers published and the number of patent applications, calculate the cumulative values of the number of scientific papers and the cumulative values of the number of patent applications year by year, input the cumulative values of the number of scientific papers and the cumulative values of the number of patent applications year by year into a computer program (such as Loglet Lab 4.0) respectively, perform S-curve fitting according to formula (1), obtain the fitting curves of time and the number of scientific papers, the fitting curves of time and the number of patent applications, and obtain the fitting parameter values, including saturation value, inflection point, growth time, determination coefficient R 2 and other parameter values, where R 2 is used to determine the S-curve fitting effect.

[0062]

[0063] Among them, K represents the saturation value, which is the limit value of the cumulative utility. During the entire life cycle, the cumulative value will infinitely approach the saturation value; t m represents the inflection point, which is the demarcation point between the growth period and the maturity period. At this point, the curve growth rate reaches the maximum value. Before this point, the growth rate continuously increases, and after this point, the growth rate gradually decreases; Δt represents the growth time, which is the time experienced by the cumulative utility from 10% of the saturation value to 90% (i.e., Δt = t 90 -t 10 ), spanning the entire growth period and maturity period.

[0064] According to the S-curve, the critical values for dividing the life cycle stages can be identified: Let t x be the time node when the cumulative utility reaches x% of the saturation value, then before t 10 is the germination period, between t 10 and t m is the growth period, between t m and t 90 is the maturity period, and after t 90 is the decline period.

[0065] The S-curve fitting results of the number of scientific papers in the field of brain-computer interfaces are as follows: Figure 3 As shown. From the fitting results, it can be seen that the basic research reflected by the scientific papers in the field of brain-computer interfaces entered the growth stage in 2013, the inflection point was in 2026, and it is expected to reach maturity by 2039, with a growth period of 25 years.

[0066] The S-curve fitting results of the number of patent applications in the field of brain-computer interfaces are as follows: Figure 4 As shown. From the fitting results, it can be seen that the technological applications reflected by the patent data in the field of brain-computer interfaces entered the growth stage in 2018, the inflection point was in 2027, and it is expected to enter the mature stage in 2035, with a growth period of 15 years.

[0067] S104: Take the development stage of basic research and the development stage of technological applications as the horizontal and vertical coordinates, and construct a life cycle matrix according to the division results of the time overlap area between the development stage of basic research and the development stage of technological applications.

[0068] Take the four stages of the germination period, growth period, mature period, and decline period of basic research as the horizontal axis, and the four stages of the germination period, growth period, mature period, and decline period of technological applications as the vertical axis to initially construct a life cycle matrix, as shown in Figure 2 As shown. Specifically, the life cycle matrix can be divided into four quadrants. If the letter b is used to represent basic research, the letter a is used to represent technological applications, and the numbers [1, 2, 3, 4] are used to represent the four stages of the germination period, growth period, mature period, and decline period respectively, then the values of the array (b, a) at different stages can be obtained, forming four regions. Among them, the region enclosed by (1, 1), (1, 2), (2, 1), and (2, 2), whether it is basic research or technological application, is in the germination and growth stage, and it can be considered that this field is an emerging field with great development potential; the region enclosed by (3, 1), (3, 2), (4, 1), and (4, 2), the basic research has matured but the technological application is still in the germination and development stage, and it can be considered that there is a "Sleeping Beauty research" in this field where the application value has not been fully realized, or it belongs to a more pure theoretical research field with unclear application value, etc.; the region enclosed by (1, 3), (1, 4), (2, 3), and (2, 4), the technological application has entered the mature stage, and the basic research is still in the germination and growth stage, indicating that the technological application in this field has gone ahead of the basic research, and further development of the field requires new theories and breakthroughs in basic research; the region enclosed by (3, 3), (3, 4), (4, 3), and (4, 4), both the technological application and the basic research have developed and matured, and future breakthroughs and developments in this field may more likely require new breakthroughs in other fields to activate and empower.

[0069] According to the data fitting results in the field of brain-computer interfaces, the critical values of the life cycle stages in this field are shown in Table 1. Among them, the starting year of the germination period is selected as the time when the cumulative utility reaches 1% of the saturation value. Further, based on the stage division data in Table 1 and Figure 2 the orthogonal matrix model of the life cycle shown, the overlapping time regions of the basic research development stage and the technology application development stage are divided:

[0070] Before 2013, both basic research and technology application were in the germination period, occupying the coordinate point (1, 1); from 2013 to 2018, basic research was in the growth period and technology application was in the germination period, occupying the coordinate point (2, 1); from 2018 to 2026, both basic research and technology application were in the growth period, occupying the coordinate point (2, 2); from 2026 to 2027, basic research was in the mature period and technology application was in the growth period, occupying the coordinate point (3, 2); from 2027 to 2035, both basic research and technology application were in the mature period, occupying the coordinate point (3, 3); from 2035 to 2039, basic research was in the mature period and technology application was in the decline period, occupying the coordinate point (3, 4); after 2039, both basic research and technology application entered the decline period, occupying the coordinate point (4, 4).

[0071] The final orthogonal matrix of the life cycle of the brain-computer interface field drawn is as Figure 5 shown.

[0072] Table 1 Critical values of the life cycle stages in the brain-computer interface field

[0073]

[0074] S105: According to the constructed life cycle matrix and the duration of each development stage, draw the evolution trend curves of the basic research and technology application stages.

[0075] Based on the constructed life cycle matrix, calculate the durations of the science and technology field in the germination period, growth period, mature period, and decline period of basic research and technology application respectively;

[0076] Combine the basic research development stage (b), the technology application development stage (a), and the duration (t) of a certain stage to form a three-dimensional array (b, a, t) to obtain the coordinate sequence of the development law. Visualize the coordinate sequence to obtain the evolution trend curves of the basic research and technology application stages.

[0077] In this embodiment, according to Figure 5 it can be calculated that the residence times of the brain-computer interface field in each development stage are respectively:

[0078] 2013 - 1999 = 14 years, corresponding to the coordinate point (1, 1);

[0079] 2018 - 2013 = 5 years, corresponding to the coordinate point (2, 1);

[0080] 2026 - 2018 = 8 years, corresponding to the coordinate point (2, 2);

[0081] 2027 - 2026 = 1 year, corresponding to the coordinate point (3, 2);

[0082] 2035 - 2027 = 8 years, corresponding to the coordinate point (3, 3);

[0083] 2039 - 2035 = 4 years, corresponding to the coordinate point (3, 4);

[0084] 2043 - 2039 = 4 years, corresponding to the coordinate point (4, 4).

[0085] If the development stage and duration are combined into a three - dimensional array, then the development stage division and prediction results in the field of brain - computer interface can be expressed as: (1, 1, 14) → (2, 1, 5) → (2, 2, 8) → (3, 2, 1) → (3, 3, 8) → (3, 4, 4) → (4, 4, 4). Taking the basic research development stage as the horizontal axis (x - axis), the technology application development stage as the vertical axis (y - axis), and the duration as the vertical axis (z - axis), visualizing the above coordinates, we get as Figure 6 shown in the curve graph of the development stage and future evolution trend in the field of brain - computer interface.

[0086] S6: According to the evolution trend curves of basic research and technology application stages, combined with the existing development evidence in the field, conduct field growth mode recognition and development law prediction.

[0087] From Figure 6 it can be seen that the brain - computer interface field has developed in the blue area for up to 27 years; in 2025, the brain - computer interface field is in the (2, 2) stage of the blue area, and the duration is expected to be 8 years; it is expected to enter the yellow area in 2026, and then both basic research and technology application will quickly enter the mature development stage. Generally speaking, in the development process of the brain - computer interface field, the gap between the basic research and technology application development stages is small, and the trend of mutual promotion and common development is obvious. The paper "Comparative Study on the Technological Competition Situation between China and the United States in the Field of Brain - Computer Interface Based on Bibliometric and Patent Analysis" by Yu Guifang et al. also points out that the United States, relying on its leading position in the field of brain - computer interface, actively promotes the deepening of basic research with application as the orientation, thus leading the continuous development of brain - computer interface technology.

[0088] Example 2

[0089] This example takes the field of quantum computing as an example to provide a recognition and prediction result of the development stage of a scientific and technological field. As Figure 1As shown, the method of Embodiment 2 includes the following steps:

[0090] S101: Determine the technical field, clarify the directions involved in the technical field, and define the specific scope with keywords.

[0091] In this embodiment, quantum computing is selected as the research field, and academic journals, conference proceedings, and authoritative research reports in the technical field are consulted; the technical field is comprehensively sorted out, the main directions and sub-fields covered by the technical field are clarified, and the research scope is accurately defined in the form of keywords.

[0092] S102: Determine the scientific paper retrieval formula and the patent retrieval formula, select a database to retrieve scientific papers and patent documents, and obtain the time series data of the scientific paper publication volume and the patent application volume;

[0093] According to the determined keywords, after multiple rounds of retrieval attempts, the retrieval formulas for scientific and technological papers and patents in the field of quantum computing are finally formed as TS = ("*quantum bit" OR "quantum superposition" OR "quantum entanglement" OR "quantum cryptography" OR "quantum password" OR "quantum turing machine" OR "quantum comput*" OR "quantum simulation" OR "topological quantum computation" OR "quantum gate" OR "superconducting quantum circuit" OR "quantum algorithm*" OR "quantum genetic algorithm" OR "shor algorithm" OR "grover algorithm" OR "HHL algorithm" OR "quantum approximate optimization algorithm" OR "quantum machine learning*" OR "quantum deep learning*" OR "quantum neural network" OR "qubit*" OR "quantum processor" OR "quantum memory" OR "quantum measurement" OR "quantum encrypt*" OR "Quantum cloud platform"); The data source of scientific and technological papers is selected as the Web of Science database, and the data source of patent applications is selected as the Derwent Innovations Index database.

[0094] Enter the retrieval formula into the selected databases respectively, and screen the date range and document type through the advanced retrieval function; Obtain the cumulative annual values of the number of scientific and technological papers and the cumulative annual values of the number of patent applications according to the retrieval results respectively.

[0095] S103: Perform S-curve fitting on the time series data of the publication volume of scientific and technological papers and the patent application volume respectively, and identify the time nodes of each development stage of the germination period, growth period, maturity period, and decline period of basic research and technological applications in the scientific and technological field; Among them, the S-curve fitting result of the time series data of the publication volume of scientific and technological papers corresponds to basic research, and the S-curve fitting result of the time series data of the patent application volume corresponds to technological application.

[0096] Based on the time - series data of the number of scientific and technological papers published and the number of patent applications, the cumulative annual values of the number of scientific and technological papers and the cumulative annual values of the number of patent applications are calculated. The cumulative annual values of the number of scientific and technological papers and the cumulative annual values of the number of patent applications are respectively input into a computer program (such as Loglet Lab 4.0) for S - curve fitting to obtain the fitting curves of time and the number of scientific and technological papers, the fitting curves of time and the number of patent applications, and obtain the fitting parameter values, including saturation value, inflection point, growth time, coefficient of determination R 2 and other parameter values.

[0097] The S - curve fitting results of the number of scientific and technological papers in the field of quantum computing are as Figure 7 shown. From the fitting results, it can be seen that the basic research reflected by the scientific and technological papers in the field of quantum computing entered the growth stage in 2006, the inflection point was in 2019, and it is expected to reach maturity by 2031, with a growth time of 24 years.

[0098] The S - curve fitting results of the number of patent applications in the field of quantum computing are as Figure 8 shown. From the fitting results, it can be seen that the technological application reflected by the patent data in the field of quantum computing entered the growth stage in 2018, the inflection point was in 2025, and it is expected to enter the mature stage in 2031, with a growth time of 13 years.

[0099] S104: Take the development stage of basic research and the development stage of technological application as the horizontal and vertical coordinates, and construct a life - cycle matrix according to the time - overlapping area division results of the development stage of basic research and the development stage of technological application.

[0100] According to the data fitting results in the field of quantum computing, the critical values of the life - cycle stages in this field are shown in Table 2, where the starting year of the germination period is the time when the cumulative utility reaches 1% of the saturation value. Further, according to the stage - division data in Table 2 and the Figure 2 shown life - cycle orthogonal matrix model, conduct the time - overlapping area division of the development stage of basic research and the development stage of technological application:

[0101] Before 2006, basic research took the lead in starting and was in the embryonic stage, occupying the coordinate point (1, 0); from 2006 to 2012, basic research continued to develop and was in the growth stage, occupying the coordinate point (2, 0); from 2012 to 2018, technology application was in the embryonic stage, occupying the coordinate point (2, 1); from 2018 to 2019, both basic research and technology application were in the growth stage, occupying the coordinate point (2, 2); from 2019 to 2025, basic research was in the mature stage and technology application was in the growth stage, occupying the coordinate point (3, 2); from 2025 to 2031, both basic research and technology application were in the mature stage, occupying the coordinate point (3, 3); after 2031, both basic research and technology application entered the decline stage, occupying the coordinate point (4, 4).

[0102] The finally drawn orthogonal matrix of the life cycle in the field of quantum computing is as Figure 9 shown.

[0103] Table 2 Critical values of the life cycle stages in the field of quantum computing

[0104]

[0105] S105: According to the constructed life cycle matrix and the duration of each development stage, draw the evolution trend curves of the basic research and technology application stages.

[0106] Based on the constructed life cycle matrix, calculate the durations of the science and technology field in the embryonic stage, growth stage, mature stage and decline stage of basic research and technology application respectively;

[0107] Combine the basic research development stage (b), the technology application development stage (a) and the duration (t) of a certain stage to form a three-dimensional array (b, a, t) to obtain the coordinate sequence of the development law, and visualize the coordinate sequence to obtain the evolution trend curves of the basic research and technology application stages.

[0108] In this embodiment, according to Figure 9 it can be calculated that the residence times of the quantum computing field in each development stage are respectively:

[0109] 2006 - 1993 = 13 years, corresponding to the coordinate point (1, 0);

[0110] 2012 - 2006 = 6 years, corresponding to the coordinate point (2, 0);

[0111] 2018 - 2012 = 6 years, corresponding to the coordinate point (2, 1);

[0112] 2019 - 2018 = 1 year, corresponding to the coordinate point (2, 2);

[0113] 2025 - 2019 = 6 years, corresponding to the coordinate point (3, 2);

[0114] 2031 - 2025 = 6 years, corresponding to the coordinate point (3, 3);

[0115] 2038 - 2031 = 7 years, corresponding to the coordinate point (4, 4);

[0116] If the development stage and the duration are combined into a three - dimensional array, then the development stage division and prediction results in the field of quantum computing can be expressed as: (1, 0, 13) → (2, 0, 6) → (2, 1, 6) → (2, 2, 1) → (3, 2, 6) → (3, 3, 6) → (4, 4, 7). Taking the basic research development stage as the horizontal axis (x - axis), the technology application development stage as the vertical axis (y - axis), and the duration as the vertical axis (z - axis), visualizing the above coordinates, we get the curve graph of the development stage and future evolution trend in the field of quantum computing.

[0117] S6: According to the evolution trend curves of basic research and technology application stages, combined with the existing development evidence in the field, conduct field growth mode recognition and development law prediction.

[0118] In this embodiment, the development time of quantum computing in the blue area is up to 26 years; in 2025, the quantum computing field is in the (3, 2) stage of the yellow area, and the duration is expected to be 6 years; it is expected to enter the red area and gradually mature in 2031. Generally speaking, in the development process of the quantum computing field, the development of basic research plays a leading role in the transition of the development stage, reflecting that basic research is relatively more advanced than technology application and plays an important leading role.

[0119] Obviously, those skilled in the art can make various changes and modifications to this application without departing from the spirit and scope of this application. Thus, if these modifications and variations of this application fall within the scope of the claims of this application and their equivalent technologies, this application also intends to include these changes and modifications.

[0120] The content not detailedly described in the specification of the present invention belongs to the well - known technology of those skilled in the art.

Claims

1. A method for identifying and predicting the stage of technological development based on a life cycle matrix, characterized in that: The following steps are involved: Determine the scientific and technological field, clarify the direction involved in the scientific and technological field, and define the specific scope with keywords; Determine the search formula for scientific papers and patents, select databases to search for scientific papers and patent documents, and obtain time series data on the number of scientific papers published and the number of patent applications; S-curve fitting is performed on the time series data of scientific paper publication and patent application respectively to identify the time nodes of the embryonic stage, growth stage, maturity stage and decline stage of basic research and technological application in the field of science and technology; among them, the S-curve fitting results of the time series data of scientific paper publication correspond to basic research, and the S-curve fitting results of the time series data of patent application correspond to technological application; Taking the basic research development stage and the technology application development stage as the horizontal and vertical coordinates, the life cycle matrix is ​​constructed according to the division results of the time overlap areas of the basic research development stage and the technology application development stage; Based on the constructed life cycle matrix and the duration of each development stage, draw the evolution trend curve of basic research and technology application stages; Based on the evolution trend curves of basic research and technological application stages, combined with existing field-related development evidence, we can identify field growth patterns and predict development laws.

2. According to claim 1, a method for identifying and predicting the technological development stage based on a life cycle matrix is ​​characterized in that: The time series data of the number of scientific papers published and the number of patent applications represent the number of scientific papers and the number of patent applications retrieved in each time period, and one year is selected as a time period, or 2 to 3 years is selected as a time period.

3. According to the method of identifying and predicting the technological development stage based on the life cycle matrix in claim 1, it is characterized in that: The S-curve fitting is performed on the time series data of the number of scientific papers published and the number of patent applications to identify the time nodes of the embryonic stage, growth stage, maturity stage and decline stage of basic research and technological application in the field of science and technology, including: According to the time series data of the number of scientific papers published and the number of patent applications, the cumulative values ​​of the number of scientific papers and the cumulative values ​​of the number of patent applications are calculated year by year. The cumulative values ​​of the number of scientific papers and the cumulative values ​​of the number of patent applications are respectively input, and the S curve is fitted according to formula (1) to obtain the fitting curves of the time and the number of scientific papers, the fitting curves of the time and the number of patent applications, and the fitting parameter values, including the saturation value, the inflection point, the growth time, the determination coefficient R 2 , where R 2 Used to determine the S-curve fitting effect; Among them, K represents the saturation value, which is the limit value of the cumulative utility. In the entire life cycle, the cumulative value will infinitely approach the saturation value; t m represents the inflection point, which is the dividing point between the growth stage and the mature stage. At this point, the growth rate of the curve reaches its maximum value. Before this point, the growth rate continues to increase, and after this point, the growth rate gradually decreases. Δt represents the growth time, which is the time it takes for the cumulative utility to grow from the saturation value of 10% to 90%, spanning the entire growth stage and mature stage. Identify the critical value of life cycle stage division based on S curve: Let t x is the time point when the cumulative utility reaches the saturation value of x%, then t 10 Before that is the budding stage, t 10 ~t m The period between is the growth period, t m ~t 90 The period between is the mature period, t 90 This is followed by a period of decline.

4. The method for identifying and predicting the technological development stage based on the life cycle matrix according to claim 3 is characterized in that: The construction life cycle matrix includes: The letter b is used to represent basic research, the letter a is used to represent technological application, and the numbers [1, 2, 3, 4] are used to represent the four stages of germination, growth, maturity and decline, respectively. The values ​​of the array (b, a) at different stages are obtained, forming a total of 16 sets of coordinate points; With t 10 ,t m ,t 90 As dividing nodes, draw the timeline of the basic research development stage and the timeline of the technological application development stage, divide the time overlapping areas of the basic research development stage and the technological application development stage, obtain all combinations of the development stages of basic research b and technological application a, and then obtain all (b, a) coordinate points occupied by this scientific and technological field to construct a life cycle matrix.

5. The method for identifying and predicting the technological development stage based on the life cycle matrix according to claim 4 is characterized in that: According to the values ​​of the array (b, a) at different stages, it is divided into four areas: In the area enclosed by (1,1), (1,2), (2,1), and (2,2), both basic research and technological application are in the embryonic growth stage, and this technology field is considered to be an emerging field with great development potential. In the area enclosed by (3,1), (3,2), (4,1), and (4,2), basic research is mature but technological application is still in the embryonic development stage, and this technology field is considered to be a field with application value but has not yet been brought into play, or a field that is more inclined to pure theoretical research and has no obvious application value. In the area enclosed by (1, 3), (1, 4), (2, 3), and (2, 4), technology application has entered the mature stage, while basic research is still in the embryonic growth stage. This shows that technology application in this scientific and technological field is already at the forefront of basic research, and further development of the field requires new theories and breakthroughs in basic research. In the area enclosed by (3, 3), (3, 4), (4, 3), and (4, 4), both technology application and basic research have matured, and future breakthroughs and development in this scientific and technological field will require new breakthroughs in other fields to activate them.

6. The method for identifying and predicting the technological development stage based on the life cycle matrix according to claim 4 is characterized in that: The drawing of the evolution trend curve of basic research and technology application stage includes: Based on the constructed life cycle matrix, the duration of the science and technology field in the embryonic stage, growth stage, maturity stage and decline stage of basic research and technological application is calculated respectively; The basic research development stage b, the technology application development stage a and the duration t of a certain stage are combined into a three-dimensional array (b, a, t) to obtain the development law coordinate sequence. The coordinate sequence is visualized to obtain the evolution trend curve of the basic research and technology application stages.

7. The method for identifying and predicting the technological development stage based on the life cycle matrix according to claim 6 is characterized in that: The identification of field growth patterns and prediction of development rules include: Identify historical development stages, identify the current development stage and the duration of the current stage, and predict when and which development stage will be entered in the future.

8. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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