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62 results about "Factor selection" patented technology

Factor Selection. The designed experiment is best applied to a situation where all known sources of variation are held constant except for those factors (main, subsidiary or blocking) in the design.

Risk assessment algorithm for information system

The invention discloses a risk assessment algorithm for an information system. According to the GB/T20984-2007 standard, a correlation between the assessment factors of assets, the assessment factors of vulnerability and the assessment factors of threats of the information system is established, a safety assessment indicator system is achieved, and 24 pairs of risk relations are achieved. The 24 pairs of achieved risk relations are substituted into a formula (1), an asset comprehensive value A is obtained through calculation. According to asset comprehensive value A and a vulnerability value V, the comprehensive value F of the loss caused by security events is worked out. According to the vulnerability value V and a threat value T, a security event possibility comprehensive value L is worked out. The comprehensive value F of the loss caused by the security events and the security event possibility comprehensive value L are substituted into a formula (2), and then a risk comprehensive value R is worked out and obtained. The risk assessment algorithm for the information system can eliminate the influence caused by the facts that assessment factor selection is unreasonable and risk correlation analysis cannot objectively reflect the system state, and improve the objectivity and the accuracy of risk assessment.
Owner:GUIZHOU UNIV

Method for selecting main substation capacity and optimal station address of transformer substation

The present invention discloses a method for selecting main substation capacity and an optimal station address of a transformer substation and belongs to the technical field of distribution network planning in the power industry. According to the present invention, a method for selecting the station address of the transformer substation comprises: selecting the optimal station address of the transformer substation according to factors such as an area load condition, load distribution, a geographic position and the like; and a method for determining the substation capacity comprises: selecting and determining the main substation capacity of the transformer substation according to the load distribution and the future development condition by considering conditions such as investment cost and the like. According to the present invention, based on the actual situations, a load is predicted and according to the load prediction condition and the actual situations of environmental geographical factors and the like, a transformer substation layout principle is combined, factors such as initial investment cost, operation cost, maintenance cost and the like of a transformer substation planning scheme are comprehensively considered and related constraint conditions such as a capacity-load ratio and the like are considered so as to determine the optimal substation capacity and station address; and the method considers more comprehensive actual factors of a distribution network transformer substation locating and sizing plan, so that the planning scheme is closer to the actual situations, the method is more reasonable and practicality is higher.
Owner:STATE GRID CORP OF CHINA +1

Credit prediction overdue method and system fused with machine learning

The invention provides a credit overdue prediction method and system fused with machine learning, and the method comprises the steps: collecting a plurality of credit factor data, carrying out the preprocessing, carrying out the calculation and sorting of the importance of the credit factor data in a preprocessing result, and deleting redundancy, and obtaining the selected credit factor data; andconstructing a training sample based on the credit factor data, establishing and training a credit overdue prediction model by using LSTM based on the training sample, determining an optimal parameter, and performing credit overdue prediction after the optimal model is obtained. According to the invention, credit factor data is widely collected to improve comprehensiveness of credit overdue prediction; the missing training data is classified to improve the data quality; the class imbalance condition of the user is processed by using an oversampling method, and data distribution is balanced; all factors influencing credit expiration is sorted, and redundancy is eliminated, and then the reasonability of factor selection is improved; and a credit overdue prediction model is comprehensively established based on bidirectional LSTM in combination with timing sequence factors, optimal model parameters are determined through S-fold intersection, and the optimal model quality is improved.
Owner:北京银联金卡科技有限公司

Robust direction of arrival (DOA) estimation method based on sparse and low-rank recovery

The invention belongs to the field of signal processing, and particularly relates to a robust direction of arrival (DOA) estimation method based on sparse and low-rank recovery. According to the technical scheme, firstly, based on a low-rank matrix decomposition method, a received signal covariance matrix is modeled as the sum of a low-rank noise-free covariance matrix and a sparse noise covariance matrix; then the convex optimization problem about a signal and noise covariance matrix is constructed based on a low-rank recovery theory; then a convex model about the sampling covariance matrix estimation error is constructed, and a convex set explicitly includes the convex optimization problem; and finally, based on the obtained covariance matrixes, DOA estimation is achieved through a MVDRmethod. In addition, based on the statistical characteristic that the sampling covariance matrix estimation error submits to progressive normal distribution, an error parameter factor selection criterion is derived to reconstruct the covariance matrixes. Numerical simulation shows that under the limited sampling conditions, compared with traditional CBF and MVDR algorithms, a proposed algorithm ishigh in DOA estimation accuracy and robust in performance.
Owner:DALIAN UNIVERSITY

FEC scheme for encoding two bit-streams

An encoding system is configured to allow data to be transmitted at one of two selectable bit-error-rate quality factors. The first bit-error-rate quality factor selection corresponds to the conventional ATSC FEC encoding systems, and the second bit-error-rate quality factor selection provides an ATSC-like FEC encoding scheme that substantially improves the bit-error-rate. The first quality factor selection effects a 2/3 trellis encoding, whereas the higher quality factor selection effects a 1/3 trellis encoding. Because the high-quality trellis encoding rate of 1/3 is half the lower-quality trellis encoding rate of 2/3, the data rate of this high-quality encoded bit-stream is half that of the conventional lower-quality encoded bit-stream. The 1/3 trellis encoding is effected using an ATSC-compatible encoding and a modified symbol mapping. The encoding scheme provides 2:1 data redundancy and the symbol mapping provides a maximum distance for the redundant encoding. By combining techniques that each decrease the likelihood of an uncorrectable error at the receiver, the substantial improvement in bit-error-rate can be achieved. At the receiver, a single trellis decoder with different metric tables is used to decode the two bit-streams, thereby providing substantial compatibility with ATSC-compatible receivers.
Owner:KONINKLIJKE PHILIPS ELECTRONICS NV

Human face feature extracting method based on active shape model and POEM (patterns of oriented edge magnituedes) texture model in complicated background

The invention relates to a human face feature extracting method based on an active shape model and a POEM (patterns of oriented edge magnituedes) texture model in the complicated background and belongs to the technical field of model identification. The human face feature extracting method includes calibrating feature points of a training set; establishing an overall shape model for training samples; establishing a POEM texture histogram for each calibrated feature point; selecting initial human face shapes of a factor selection model according to the shape model; calculating the POEM histogram of each candidate feature point in a test image; calculating similarity of the candidate feature points and target points of the histogram by the mahalanobis distance function; performing iterative search matching by downloading initial human faces into the model; secondarily extracting local organs or human face outlines with poor extraction effect. By the human face feature extracting method, robustness of changes of complicated environments (such as posture, light and expression) is improved, high extraction accuracy is obtained, and the human face feature extracting method has good application prospect.
Owner:CHONGQING UNIV OF POSTS & TELECOMM

Disclosed is a traffic accident data intelligent analysis and comprehensive application system

ActiveCN109409430AFlexible accident attribute factor screening functionEffectively deal with inconsistent attribute factorsDigital data information retrievalDetection of traffic movementMissing dataData source
The invention provides a traffic accident data intelligent analysis and comprehensive application system. The system comprises a data docking module, a mining processing module, an interaction module,a map module and a data analysis module, the mining processing module drives data processing through a traffic accident data factor importance analysis model according to traffic accident data extracted by the data docking module, and the importance degree of attribute factor set elements is obtained; the data analysis module receives an attribute factor selection result of the interaction module, takes an attribute factor as a data analysis angle, and provides a targeted data analysis result through an accident data analysis mode; according to the system, importance analysis of attribute factors is carried out based on original traffic accident data, a missing data estimation strategy is configured, and the situation that the attribute factors provided by different data sources of a traffic accident are inconsistent can be effectively coped with; therefore, attribute factors with important traffic accident information are extracted from the sample data selected by the user, and quantitative importance indexes are output.
Owner:JIANGSU ZHITONG TRANSPORTATION TECH

Variable class remote sensing image segmentation method based on optimal fuzzy factor selection

The invention provides a variable class remote sensing image segmentation method based on optimal fuzzy factor selection. The method comprises: reading a to-be-segmented remote sensing image; determining an optimal homogeneous region class number of the to-be-segmented remote sensing image; finding the homogeneous region class of each pixel spectrum measurement vector in the to-be-segmented remote sensing image through de-fuzzification, and obtaining a segmentation result of the to-be-segmented remote sensing image. The method adopts the partition entropy index as the index of a preferable fuzzy factor. When the fuzzy factor of the to-be-segmented remote sensing image is smaller than the optimal fuzzy factor, a PE index is larger. When the fuzzy factor is just equal to the optimal fuzzy factor, the PE index jumps to a smaller value, and the PE index becomes stable gradually when the number of fuzzy factors further increases. The corresponding minimum fuzzy factor when the PE index converges is selected to be the optimal fuzzy factor. The class number corresponding to the optimal fuzzy factor is the optimal class number, so that the class number of homogeneous regions in the remote sensing image is determined, and a better segmentation result can be obtained.
Owner:LIAONING TECHNICAL UNIVERSITY

POOL-mechanism-based cluster regulation algorithm for target tracking in WSN (Wireless Sensor Network)

A POOL-mechanism-based cluster regulation algorithm for target tracking in WSN (Wireless Sensor Network) belongs to the technical field of wireless sensor networks and is used for target tracking in a wireless sensor network. In the traditional algorithm for target tracking, when the target moves slowly or is in the process of approximating stillness, a cluster head node consumes energy too quickly for serving as the cluster head for a long time, so that energy hole is caused easily. The algorithm provides a cluster head rotation mechanism based on a POOL mechanism; during the process of tracking a target with a variable motion in the wireless sensor network, a threshold value is set at the time when a tracking node serves as the cluster head, and when the set time is up, another node is selected from a POOL (a cluster head pool) to serve as a new cluster head according to the factors such as surplus energy, the RSSI (Received Signal Strength Indication) aparts from a target node, and the like. During the process of variable motion of the target, the structure of the POOL and the data update unceasingly. The mechanism ensures smooth transfer of the cluster head and can reduce energy consumption and prolong the service life of the network while ensuring the tracking accuracy.
Owner:SHANDONG UNIV

Timing generator and methods thereof

A timing generator and methods thereof are provided. In a first example method, a timing control signal may be produced by generating a base clock signal and a higher delay resolution clock signal, a clock cycle of the higher delay resolution signal being less than a clock cycle of the base clock signal. A first control word output signal may be generated by synchronizing a control word with the base clock signal. A second control word output signal may be generated by synchronizing the first control word output signal with the higher delay resolution clock signal and generating at least one additional control word output signal based on the second control word output signal and the higher delay resolution clock signal, the first, second and at least one additional control word output signal each having different delay resolutions. In a second example method, a timing control signal may be produced by generating a plurality of control word output signals, each of the plurality of control word output signals having a different delay resolution and selecting one of the plurality of control word output signals based on a delay resolution of the selected control word output signal, the delay resolution of the selected control word output signal better suited for interaction with an external device than delay resolutions of other of the plurality of control word output signals. A timing generator may be configured to perform either of the above-described first and second example methods.
Owner:SAMSUNG ELECTRONICS CO LTD

Partial transmission sequence peak-to-average ratio suppression algorithm of boundless information suitable for spare underwater acoustic OFDM communication system

The invention provides a partial transmission sequence peak-to-average ratio suppression algorithm of boundless information suitable for a spare underwater acoustic OFDM communication system, in particular relates to a method for solving the problem that the PTS algorithm needs to transmit side information through the adoption of the inherent sparsity of an underwater acoustic channel and the side information blind detector based on the matching pursuit channel reconstruction technology. The pectinate pilot frequencies distributed at different positions are used for carrying weighting factor selection information, and the matching pursuit technology is used for reconstructing the received different pilot frequency domain responses, and the high-reliability weighting factor blind detection can be realized through the combination with the inherent sparsity of the shallow sea underwater acoustic channel, the reliability of the communication system is guaranteed. Since the matching pursuit channel reconstruction technology adopted in the invention needs less pectinate pilot frequency number and is free from uniform; compared with the traditional PTS algorithm, the improved PTS peak-to-average ratio suppression algorithm has better PAPR suppression performance; and meanwhile, the communication frequency band utilization rate and the communication efficiency are further improved; the algorithm is suitable for the underwater acoustic communication system in resource shortage.
Owner:HARBIN ENG UNIV

Vegetable harvesting cutter cutting factor selection testing platform

The invention discloses a vegetable harvesting cutter cutting factor selection testing platform. A vegetable fixing part is used for fixing vegetables on a testing operating table by virtue of a clamping bolt and rightly adjusting the positions of the vegetables; a vegetable clamping and extracting part is used for clamping the vegetables by adjusting the distance between adjustable clamping claws and adjusting a rotating angle of a clamping plate fixed shaft; a cutter harvesting cutting part is used for adjusting a slip cutting angle of a cutter and the vegetable cutting height by adjusting an angle between an adjustment angle adjusting block and a horizontal plane and adjusting the height from a vegetable fixing plate; the cutting speed of the cutter is controlled by adjusting the speed of stepping a synchronous belt on a linear sliding table; cutting force of the cutter is measured by using a force measuring sensor; and after being completely cut, the clamped vegetables are lifted by the vegetable clamping and extracting part. According to the vegetable harvesting cutter cutting factor selection test platform disclosed by the invention, comprehensive factors of vegetable harvesting cutting can be selected, optimal cutting factors can be determined, and the success rate and yield of a vegetable harvesting process can be increased; and the testing platform is easy to operate and strong in practicability.
Owner:BEIJING UNIV OF TECH
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