51results about How to "Objective evaluation" patented technology

The invention provides a road line selection optimization method, system and device based on AI and quantitative parameter constraint, and a storage medium. The method comprises the following steps: establishing a road line selection initial preset parameter library; a high-precision remote sensing technology, an unmanned aerial vehicle, a GIS database and a traffic monitoring system are utilized to collect quantitative data, and data preprocessing is automatically carried out; a deep learning model is developed and trained, parameter values in historical cases are automatically identified and calculated, the identified and calculated parameters are trained and learned, and a deep learning result is fed back to a quantitative parameter set; a multi-factor target evaluation index system is constructed, and evaluation index values of all candidate schemes are obtained; and providing a decision support tool to help a user to understand the advantages and disadvantages of each scheme and recommend an optimal line scheme meeting all quantitative parameter constraints. According to the invention, the line selection efficiency and accuracy can be improved, the compliance of the line selection scheme in the aspects of technology, safety, environment and the like is ensured, and an efficient, economic and environment-friendly line selection scheme is provided for a road construction project.

The invention provides a multi-station space-time correlation photovoltaic output probability prediction method and system based on interpretable deep learning, and relates to the field of photovoltaic power generation intelligent prediction. According to the method, a photovoltaic field station group output two-dimensional matrix is constructed based on photovoltaic output historical data, column vectors in the two-dimensional matrix serve as correlation test objects, and automatic typing is carried out on the correlation test objects. Fitting a probability distribution function corresponding to the photovoltaic output historical data after typing by using a non-parametric kernel density estimation method; and sorting out data containing space-time correlation information of the photovoltaic stations from the two-dimensional matrix, constructing a multi-station joint input matrix, and sending the multi-station joint input matrix into a bidirectional gating circulation unit for training to obtain an optimal photovoltaic output prediction model. And the model is used to complete photovoltaic output determinacy prediction in the future, and a probability prediction method is used to carry out uncertainty quantification on photovoltaic output. On the basis of data typing, kernel density estimation modeling is independently carried out for each type, the noise influence is reduced, and more accurate probability prediction is provided.

The invention relates to a new energy automobile energy consumption evaluation method based on typical climate characteristics. The method comprises the following steps: step 1, establishing a typical climate region model; 2, establishing a typical test scene in combination with typical climate conditions; step 3, collecting power consumption data of the vehicle in different test scenes; and 4, energy consumption analysis and evaluation: establishing an energy consumption model, and analyzing the energy consumption condition in each typical test scene. According to the method, the energy consumption of the new energy vehicle in different use scenes can be comprehensively evaluated based on the typical climate characteristics, so that the evaluation is more objective and closer to the real use feeling of a user.

The invention relates to a refined prediction method and device for goaf stability and a storage medium, and the method comprises the steps: constructing a block model and a three-dimensional geological model, and enabling the three-dimensional geological model to coincide with the block model; performing rock mass mechanical characterization on the exploration mine to obtain rock mass mechanical parameters of the block body model; based on the block model, the three-dimensional geologic model and the rock mass mechanical parameters, constructing a rock mass refined numerical calculation model; carrying out numerical simulation on the surrounding rock stability of the goaf by adopting a rock quality refined numerical calculation model to obtain a rock quality numerical simulation result; determining a plurality of stability evaluation indexes of the goaf according to the exploration information of the exploration mine, the rock mass mechanical parameters and the rock mass numerical simulation result; and determining the stability membership degree and the stability prediction grade of the goaf based on the plurality of stability evaluation indexes of the goaf. The stability of the goaf is evaluated comprehensively and objectively, and the accuracy of stability prediction of the goaf is improved.

The invention provides a sanitation work evaluation method based on an MRS-YOLO model, and belongs to the field of machine vision. Firstly, an existing target detection training method SlideLoss is improved, a SlideLossIOU method is provided, and the small target recognition capability is remarkably improved. Secondly, a multi-dimensional convolution mechanism and a dynamic convolution mechanism are adopted, a YOLO model feature extraction method is optimized, and model robustness is enhanced; and finally, a Transform mechanism is introduced, so that the model detection precision and the feature utilization rate are further improved, and meanwhile, the calculation cost is reduced. Compared with a traditional detection method, the garbage can be detected, and a scientific and objective environmental sanitation work evaluation method can be provided by calculating and analyzing a garbage identification result. The MRS-YOLO model has better robustness, higher reasoning speed and higher detection precision, high-efficiency and low-cost intelligent garbage classification is realized, and reliable data support is provided for environmental sanitation work management.

The invention relates to the field of geothermal geology, in particular to a geothermal resource evaluation method, device and equipment based on machine learning. Comprising the following steps: acquiring geological data of a plurality of observation points selected in a first geothermal exploration area; selecting a second geothermal exploration area according to the geological data of a plurality of observation points in the first geothermal exploration area; acquiring a data set of a plurality of well drilling points in the second geothermal exploration area; training a geothermal parameter prediction model and a geothermal resource evaluation model according to the data sets of the plurality of well drilling points; and obtaining a geothermal resource evaluation result of the first geothermal exploration area by using the geothermal parameter prediction model and the geothermal resource evaluation model obtained by training according to the geological data of the plurality of observation points. According to the embodiment of the invention, the ability of predicting geothermal parameters and evaluating geothermal resources according to geological data is learned by using the machine learning model, the accuracy of geothermal resource exploration under the condition of lack of drilling data is improved, and the method has important significance for delineation and division of favorable areas of geothermal resource exploration.

The invention discloses an ankylosing spondylitis exercise rehabilitation management system. A first acquisition module acquires an exercise rehabilitation scheme corresponding to a user; the second acquisition module acquires motion data of the user based on the mobile medical equipment; the determination module determines the exercise standard degree of the user based on the exercise data and the exercise rehabilitation scheme; the management module sends an exercise prompt to the user when the exercise standard degree does not reach a preset standard degree threshold value, and the exercise standard degree of the user is determined by comparing the exercise data of the patient user with the exercise rehabilitation scheme, so that the exercise condition of the patient user is objectively and accurately evaluated, and the user experience is improved. The exercise behavior of the patient user is effectively managed based on the evaluation result, effective implementation of exercise rehabilitation is guaranteed, the exercise data of the patient user is collected through the mobile medical equipment, subjective deviation of self recording of the user is avoided, the accuracy and reliability of exercise data collection are effectively guaranteed, and the user experience is improved. And the accuracy and reliability of the evaluation result are improved.

The embodiment of the invention provides a vehicle drivability evaluation method and system, electronic equipment and a storage medium, and belongs to the technical field of automobile engineering. The method comprises the steps that when it is determined that a vehicle is in a constant acceleration working condition, a vehicle longitudinal acceleration disturbance scoring index, a high-frequency disturbance frequency and amplitude proportion scoring index, a longitudinal acceleration gradient scoring index, an expected acceleration scoring index, an accelerator map matching degree scoring index and a low-frequency resonance scoring index are calculated; based on the vehicle longitudinal acceleration disturbance scoring index, the high-frequency disturbance frequency and amplitude proportion scoring index, the longitudinal acceleration gradient scoring index, the expected acceleration scoring index, the accelerator map matching degree scoring index and the low-frequency resonance scoring index, calculation is conducted according to preset weights, and a drivability evaluation score is obtained. By combining multi-dimensional and quantitative evaluation indexes, accurate evaluation of the acceleration performance of the AMT heavy truck is realized, the evaluation consistency and efficiency are improved, and the evaluation cost is reduced.

The invention discloses a hospital research and development project approval evaluation method based on big data analysis, and the method is characterized in that the method comprises the specific steps: S1, obtaining data from a related data source of a target hospital, the data source comprises one or more of a hospital official website, a scientific research project declaration system, a medical resource management system and national and local scientific research project management platforms; s2, screening and determining evaluation indexes, and screening out key evaluation indexes from the obtained data; the invention belongs to the technical field of data processing, processes of data collection, preprocessing, analysis, calculation and the like are automatically completed through a big data analysis technology, and the approval period is greatly shortened, so that the approval efficiency is improved; based on a scientific evaluation model and a big data analysis technology, the potential and value of each application project are objectively and comprehensively evaluated, and human intervention and subjective judgment are reduced, so that the examination and approval accuracy is improved.

The invention provides a high performance liquid chromatography analysis method of vitamin D drop related substances. A two-dimensional liquid chromatography detection method is adopted, interference of oily matrixes in the vitamin D drops is avoided, and related substances in the vitamin D drops can be accurately detected. The analysis method disclosed by the invention is stable in baseline, good in stability, good in specificity and high in sensitivity, so that the product quality is comprehensively, accurately and objectively evaluated, and the analysis method has very important significance.

The invention discloses a supplier evaluation method and equipment based on a data sharing mechanism, and a medium, belongs to the technical field of supply chain management, and aims to solve the technical problem of how to realize data sharing and intercommunication among different service systems, carry out comprehensive, scientific, objective and accurate grade division on suppliers, and improve the evaluation efficiency of the suppliers. In order to improve the efficiency and effect of supply chain management, the technical scheme adopted by the invention comprises the following steps of: constructing a data sharing platform: according to sharing requirements among departments, integrating data resources of each business system according to a unified format, and taking a standardized data directory and data resources as a basis; according to assessment rules and requirements, different evaluation indexes are selected, scheme making is completed, a weight is distributed for evaluation factors in an evaluation index system, and the importance of the evaluation factors in comprehensive evaluation is reflected; establishing an assessment personnel pool, and randomly distributing assessment personnel for different suppliers; performing assessment scoring and data collection; performing comprehensive scoring; and grade calculation and assessment result application.

The present invention relates to the field of detection technology, and specifically to a bearing operation roundness fluctuation detection device and detection method. The bearing operation roundness fluctuation detection device comprises: a detection frame, fixedly mounted on a working base, and the detection frame is used for support and installation. A clamping member, mounted on the working base, and the clamping member is used to clamp the placed bearing, so as to fix the outer ring of the bearing to be detected. A rotating detection member is mounted on the detection frame, and is used to be inserted into the inner ring of the placed bearing, and rotate the inner ring of the bearing by rotation. A tension sensor, which is used to sense the deflection centrifugal force F of the rotating detection member. A controller, the controller is used to control the clamping member to fix the outer ring of the bearing, the rotating detection member to perform detection, and obtain the deflection centrifugal force F through the tension sensor. This method can be used to determine whether the fluctuation within the radial pressure bearing capacity of the bearing is qualified, has strong evaluation capabilities, and is suitable for the bearing use environment.

The evaluation system comprises a service efficiency evaluation index module, a service efficiency evaluation standard module and an insurance institution evaluation standardization module, the service efficiency evaluation index module is used for screening the requirements of laws and regulations and regulations, acquiring data from government supervision units, insurance companies and enterprises, and extracting indexes influencing the safety responsibility insurance service efficiency from the requirements and the data; in conclusion, the evaluation method provided by the invention can enhance the attention degree of the insurance service institution on the safety responsibility insurance work, and supervise and urge the insurance service institution to check weak links in the work of the insurance service institution according to the evaluation method; in addition, the evaluation standard is beneficial for the competent department to supervise the responsibility insurance, the competent department can supervise and manage the responsibility insurance service work of the insurance institution according to the evaluation standard, it is ensured that the insurance service institution carries out business according to regulations, and the healthy development of the responsibility insurance market is ensured.

The invention discloses a water conservancy industry data index management method and device and a medium, and belongs to the technical field of big data. The method comprises the following steps: connecting a plurality of water conservancy related databases to obtain business requirements, business indexes and technical indexes in the plurality of water conservancy related databases; processing the business requirements, the business indexes and the technical indexes based on a preset natural language processing algorithm to generate a standard index database; wherein the standard index database comprises a business database and a technical database; obtaining a to-be-processed business demand, and processing the to-be-processed business demand and the standard index database based on a natural language processing algorithm to generate a to-be-processed technical index; managing the to-be-processed technical indexes based on a preset index management platform; and evaluating the to-be-processed technical index based on a preset index evaluation standard. According to the method, the water conservancy data among the multiple databases can be integrated, the index definition is unified, and the reusability of the water conservancy data is improved.

The application discloses a kind of based on big model's exclusive team performance portrait generation and intelligent evaluation system, belong to artificial intelligence and performance management technical field.The system includes data acquisition module, index system management module, performance calculation engine module, portrait generation module, big model intelligent analysis module and visual display module.Index system adopts four-level structure, including six first-level indexes, twenty-four second-level indexes, fifty-eight third-level indexes and a number of fourth-level indexes.Performance calculation engine is based on difference ratio method to calculate index score, portrait generation module generates radar chart, star rating and ranking, and big model intelligent analysis module is based on big language model to carry out intelligent evaluation and ability analysis.The application realizes the scientificity, intelligentization and visualization of exclusive team performance management, and provides strong support for exclusive team construction decision.

The invention provides a high performance liquid chromatography analysis method of maxacalcitol related substances. By changing the mobile phase, changing the type of the chromatographic column and adjusting the column temperature, the separation degree of a main peak and a plurality of related impurities is improved, related substances in maxacalcitol can be accurately detected, and the separation effect is outstanding. The analysis method disclosed by the invention is stable in baseline, good in stability, good in specificity and high in sensitivity, and has very important significance for comprehensively, accurately and objectively evaluating the product quality.

The present invention provides a method for evaluating the diffusion behavior of a regeneration agent when mixing and regenerating old asphalt based on non-equilibrium molecular dynamics simulation. Through stretching dynamics simulation, the dynamic process before the system reaches equilibrium during mixing and a period of time thereafter is more realistically simulated, and the non-equilibrium dynamic characteristics of the system are obtained. The gyration radius and diffusion coefficient of the regeneration agent calculated based on the obtained non-equilibrium dynamics trajectory can more objectively evaluate the diffusion behavior of the regeneration agent. The advantage of the present invention is that the mixing process is simulated more realistically by using non-equilibrium dynamics. In addition, after the mechanical mixing is completed, the mixed system is still in a non-equilibrium state, and the further diffusion of the regeneration agent is also described by NVT ensemble dynamics simulation. Therefore, these two steps of non-equilibrium dynamics simulation better achieve the reproduction of the fusion process of old asphalt and regeneration agent at the nanoscale on a macro scale, and can provide a more accurate and realistic characterization of the diffusion properties and behavior of the regeneration agent.

The present application discloses a PCB defect detection method, system, device and storage medium, which belongs to the field of defect detection technology. The method comprises: obtaining a PCB data set to preprocess the image of the obtained PCB data set; constructing a YOLO-v10n network model, and modifying the SPPF module in the YOLO-v10n network model to an EASPF module; constructing a feature fusion network BiFPN, and passing the extracted features into the feature fusion network BiFPN; adding an adaptive MBAM attention mechanism module between the backbone network and the feature fusion network BiFPN; inputting the PCB data set into the improved YOLO-v10n network model for pre-training to obtain the optimal weight; detecting the image to be detected according to the optimal weight, evaluating the detection result, and realizing the detection of PCB defects; by constructing and improving the YOLO-v10n network model, the accuracy of PCB defect detection is improved and the missed detection rate is reduced.

The invention relates to the technical field of carbon dioxide geological sequestration, and discloses a carbon dioxide geological sequestration quantity grading and evaluating method, system and device and a medium. A carbon dioxide sequestration efficiency coefficient influenced by process technical conditions and a carbon dioxide sequestration economic efficiency coefficient influenced by policies, laws and regulations and economic conditions are considered, and progressive carbon dioxide sequestration quantity evaluation is performed on a to-be-evaluated region, so that the geological carbon dioxide sequestration quantity can be evaluated more objectively and systematically; the evaluation precision of the geological storage amount of carbon dioxide is greatly improved, and effective and reliable data guidance is provided for development of geological storage work of carbon dioxide.

The application discloses a CDC shock absorber whole vehicle abnormal sound quantification method, device, equipment and medium, relates to the automobile NVH test and diagnosis technical field, and the method comprises the following steps: obtaining subjective evaluation based on abnormal sound perception, vibration signals and sound signals measured by sensors under different driving conditions; obtaining vibration characteristic values based on the vibration signals, obtaining sound characteristic values based on the sound signals, and converting the subjective evaluation into standardized subjective score values; calculating standardized vibration values and standardized sound values, and calculating an abnormal sound comprehensive quantification index in combination with the standardized subjective score values; dividing the abnormal sound levels based on the abnormal sound comprehensive quantification index, combining the divided abnormal sound levels and the vibration characteristic values, and outputting adjustment suggestions for the CDC shock absorber. The application realizes objective and accurate quantification of the abnormal sound degree through multi-source data fusion and characteristic frequency analysis.

The present invention discloses a method and system for evaluating the quality of service in public places based on multimodal fusion, and relates to the technical field of multimodal fusion. The method for evaluating the quality of service includes obtaining sound information in a service window environment and voice information of a customer and a service personnel; processing the sound information to obtain sound events in the sound information; processing the voice information to obtain words related to the quality of service in the voice information and words related to the quality of service in text information; the text information is information obtained after the voice information is converted into text; the sound events in the sound information, the words related to the quality of service in the processed voice information, and the words related to the quality of service in the text information are integrated to obtain a service quality grade. The present invention integrates the sound information, voice information, and text information to evaluate the service quality, thereby achieving the comprehensiveness and objectivity of the service quality evaluation.

The invention relates to a fully-mechanized excavation face dust fall effect evaluation method, and belongs to the technical field of coal mine operation. The method comprises the following steps: selecting a range 50m from the head of a fully-mechanized excavation face, and dividing the fully-mechanized excavation face into three areas according to a dust concentration rule: an area I with the dust concentration higher than 200mg / m < 3 >, and the length of the area I being l1; the dust concentration of the region II is 50-200mg / m < 3 >, and the length of the region II is 12; the dust concentration of the region III is lower than 50mg / m < 3 >, and the length of the region III is 13. The dust control effect of the fully-mechanized excavation face can be evaluated by establishing the evaluation relation between the dust control and removal effect and the regional distribution and the dust fall concentration. Therefore, monitoring and improvement of dust control measures of the fully-mechanized excavation face are facilitated, and cleanliness and safety of the working environment are improved.

The embodiment of the invention relates to the technical field of vehicle testing, and discloses a driving shaft starting and reversing abnormal sound testing method and system, and the method comprises the steps: determining a rack torque load and a loading frequency threshold value based on the load spectrum data of a driving shaft assembly of a real vehicle road test; a hub and a driving shaft assembly are installed through the test bench; wherein the driving shaft assembly is connected with the wheel hub, and the wheel hub and the driving shaft assembly are respectively connected with the test bed; loading torque to the hub according to the rack torque load, recording the actual loading times of the torque, and collecting sound generated at the joint of the hub and the driving shaft assembly; and if the actual torque loading times when the decibel of the sound is larger than the preset threshold value is smaller than the loading time threshold value, it is determined that the starting and reversing abnormal sound performance of the driving shaft assembly is unqualified. According to the technical scheme, whether the abnormal sound performance of the driving shaft assembly is qualified or not can be visually determined, and the abnormal sound problem can be found in the initial stage of design.

The invention discloses a pure highland barley powder extrusion puffing process optimization method, and belongs to the technical field of food extrusion processing. According to the method, the technical problems that the high-fiber highland barley powder is easily subjected to insufficient puffing and too hard texture in the extrusion process, and the retention rate of heat-sensitive functional components such as beta-glucan is low are solved. The method comprises the following steps: optimizing process parameters based on a multi-target response surface method, and determining the water content of materials, the temperatures of a first region, a second region, a third region and a fourth region of a machine barrel and the rotating speed of a screw; carrying out low-temperature superfine grinding on the highland barley powder; a compound emulsifier and edible sodium bicarbonate are added during hardening and tempering; during extrusion, the temperature gradient between the third area and the fourth area is controlled to be smaller than or equal to 20 DEG C; the method is mainly used for producing the high-quality pure highland barley puffed food, the puffing rate and the beta-glucan retention rate of the product can be synergistically improved, the hardness of the product is effectively controlled, and the eating quality and the nutritional value are improved.

The invention discloses a health evaluation method and device for a water supply system of a single-village water station, electronic equipment and a medium. The health evaluation method comprises the following steps: constructing a health evaluation index system of the water supply system of the single-village water station; determining actual values of indexes in the health evaluation index system to obtain a normalized actual value matrix; threshold values of indexes in the health evaluation index system are determined, and a normalized threshold value matrix is obtained; the similarity between the two matrixes is calculated based on the Euclidean distance, a health evaluation index matrix of the single-village water station water supply system is formed, an evaluation model is constructed based on the health evaluation index matrix, the health value of the single-village water station water supply system is calculated, and then the health condition of the single-village water station water supply system is evaluated according to the standard. Multi-source sensing information can be fused, health evaluation of the single-village water station water supply system is carried out based on the whole social water circulation process, the influence of human subjective factors on health evaluation is reduced, the objectivity and practicability of the health evaluation method are guaranteed, and the method has the advantages of being simple in evaluation process, high in speed, high in precision and the like.

The application belongs to the technical field of locomotive driver ergonomics. The application provides a virtual reality-based evaluation system for the fatigue of a locomotive driver. The disclosed embodiment builds a highly simulated driving scene, simulates long-time and high-intensity driving tasks, reproduces various situations that may cause driver fatigue in a risk-free manner, and monitors and analyzes the physiological response, behavioral change and psychological state of the driver in the simulation process in real time through high-precision equipment, effectively solving the problems of lack of accuracy and real-time of the existing evaluation methods, and timely and accurately evaluating and finding the fatigue degree of the locomotive driver in the task execution process, thereby providing safety guarantee for locomotive driving.

The invention relates to the technical field of underground engineering grouting, in particular to a flowing water grouting plugging performance quantitative evaluation method based on micro-fluidic fluorescence imaging, which comprises the following steps: calibrating grout with different known concentrations by using a fluorescent tracer agent to establish a quantitative relation model; carrying out a flowing water grouting test in the micro-fluidic chip so as to capture a fluorescence image sequence in the slurry migration and plugging process; inverting the fluorescence image sequence into a slurry concentration spatio-temporal evolution field based on a quantitative relation model; identifying the slurry-flowing water interface in the spatio-temporal evolution field of the slurry concentration, and tracking the dynamic evolution process of the slurry-flowing water interface to calculate the formation time of the slurry-flowing water interface and the spatio-temporal evolution law of the slurry concentration; and calculating a plugging strength index according to the slurry concentration spatio-temporal evolution field and the slurry-flowing water interface forming time, and evaluating the plugging efficiency of the grouting material by using the plugging strength index. Therefore, the problems that in an existing flowing water grouting technology, the plugging process is invisible, and key performance is difficult to quantify are solved.

The present invention belongs to the field of engineering risk assessment. The present invention provides a method and system for evaluating power distribution network engineering based on a distributed file system, which obtains relevant data; pre-processes the acquired relevant data, uses a distributed file system to store the differentially removed relevant data in a distributed manner, and performs secondary processing of the corresponding data in a distributed manner to form a data set; extracts feature information from the data set, and uses a pre-trained decision tree model to predict the transaction risk level under different feature information; constructs a curve chart or benefit map based on the feature information and prediction results of the decision tree model. The present invention can accurately evaluate the investment benefits of power distribution network engineering by conducting comprehensive data collection and analysis on investment projects, combined with economic indicators and risk assessment, and provide scientific basis for decision makers, and conduct real-time monitoring and adjustment to improve the efficiency and results of the project.

The invention discloses a Chinese language and literature handwritten calligraphy style automatic identification and scoring system and method, and relates to the technical field of image data processing, and the system comprises a standard template construction module which is used for constructing a template containing all typical Chinese language and literature handwritten calligraphy style samples; the feature extraction module comprises an acquisition unit and a feature extraction unit, the acquisition unit is used for acquiring handwritten Chinese character pictures, and the feature extraction unit is used for extracting feature information from the handwritten Chinese character pictures; the feature information extracted by the feature extraction unit comprises macroscopic level features, mesoscopic level features and microscopic level features of handwritten Chinese character pictures; by constructing the standard templates containing the typical calligraphy styles in the past, the templates not only contain the visual features of the calligraphy works, but also contain the style features, so that the templates can evaluate the calligraphy works more objectively, and the dependence on the personal experience of calligraphy experts is reduced.

The invention relates to a thin film curling technology, and discloses a thin film curling evaluation method, a thin film curling evaluation device and a polyvinyl alcohol thin film. The curl evaluation method comprises the following steps: soaking a film sample in a test solvent, and determining a curl time coefficient A, a curl direction coefficient B and a curl swelling rate coefficient C of the film sample in the test solvent; the curling coefficient omega of the thin film in the test solvent is calculated through the curling time coefficient A, the curling direction coefficient B and the curling swelling rate coefficient C, and the curling degree of the thin film is evaluated through the curling coefficient omega. According to the evaluation method, the curling degree of the film is quantified by using the curling coefficient, evaluation is more objective and accurate, the processing technology can be guided, the curling degree of the film can be reduced, and flaws such as wrinkles, creases and bubbles of subsequent products can be reduced.