A general evaluation system for optimal selection performance of radar clutter model

The optimal selection of radar clutter model is the premise of target detection,tracking,recognition,and cognitive waveform design in clutter background.Clutter characterization models are usually derived by mathematical simplification or empirical data fitting.However,the lack of standard model labels is a challenge in the optimal selection process.To solve this problem,a general three-level evaluation system for the model selection performance is proposed,including model selection accuracy index based on simulation data,fit goodness indexs based on the optimally selected model,and evaluation index based on the supporting performance to its third-party.The three-level evaluation system can more comprehensively and accurately describe the selection performance of the radar clutter model in different ways,and can be popularized and applied to the evaluation of other similar characterization model selection.

The suitability assessment on site selection for bottom seeding scallop culture based on analytic hierarchy process

Scallop culture is an important way of bottom-seeding marine ranching,which is of great significance to improve the current situation of fishery resources.However,there are some problems in site-selection evaluation of marine ranching,such as imperfect criteria system,complex structure,untargeted criteria quantification,etc.In addition,no site-selection evaluation method of bottom-seeding culture areas for scallops is available.Therefore,we established a hierarchy structure model according to the analytic hierarchy process(AHP)theory,in which social,physical,chemical,and biological environments are used as main criteria,and marine functional zonation,water depth,current,water temperature,salinity,substrate type,water quality,sediment quality,red tide,phytoplankton,and zooplankton are used as sub-criteria,on which a multi-parameter evaluation system is set up.Meanwhile,the dualism method,assignment method,and membership function method were used to quantify sub-criteria,and a quantitative evaluation for the entire criteria was added,including the evaluation and analysis of two types of unsuitable environmental situations.By overall consideration in scallop yield,quality,and marine ranching construction objectives,the weight of the main criteria could be determined.Five grades in the suitability corresponding to the evaluation result were divided,and the Python language was used to create an evaluation system for efficient calculation and intuitive presentation of the evaluation outcome.Eight marine cases were simulated based on existing survey data,and the results prove that the method is feasible for evaluating and analyzing the site selection of bottom-seeding culture areas for scallops under various environmental situations.The proposed evaluation method can be promoted for the site selection of bottom-seeding marine ranching.This study provided theoretical and methodological references for the site selection evaluation of other types of marine ranching.

A preliminary site selection system for underground hydrogen storage in salt caverns and its application in Pingdingshan,China

Large‐scale underground hydrogen storage(UHS)provides a promising method for increasing the role of hydrogen in the process of carbon neutrality and energy transition.Of all the existing storage deposits,salt caverns are recognized as ideal sites for pure hydrogen storage.Evaluation and optimization of site selection for hydrogen storage facilities in salt caverns have become significant issues.In this article,the software CiteSpace is used to analyze and filter hot topics in published research.Based on a detailed classification and analysis,a“four‐factor”model for the site selection of salt cavern hydrogen storage is proposed,encompassing the dynamic demands of hydrogen energy,geological,hydrological,and ground factors of salt mines.Subsequently,20 basic indicators for comprehensive suitability grading of the target site were screened using the analytic hierarchy process and expert survey methods were adopted,which provided a preliminary site selection system for salt cavern hydrogen storage.Ultimately,the developed system was applied for the evaluation of salt cavern hydrogen storage sites in the salt mines of Pingdingshan City,Henan Province,thereby confirming its rationality and effectiveness.This research provides a feasible method and theoretical basis for the site selection of UHS in salt caverns in China.

Vendor Evaluation and Selection Using Fuzzy AHP

Vendor evaluation and selection is one of the most important issues in manufacturing management. It is a multi-criteria decision problem including various factors. Traditional methods have many shortcomings. Fuzzy AHP model is established to solve this problem. A general evaluation method is provided and steps are presented. As a case study,the model is implemented in an electro-mechanical product company. And a detailed example is given to illustrate the effectiveness of this approach.

Selection Method of Evaluation Indicators with Three-Parameter Interval Grey Number

The evaluation problem with three-parameter interval grey number (T-PIGN) widely exists in real world. To select effective evaluation indicators of the problem, this paper puts forward evaluation index system selection principle of T-PIGN based on distance entropy model, and gives out evaluation index system selection judgment criterion of T-PIGN. Furthermore, for the redundancy of evaluation index system with T-PIGN, a selection method of evaluation index system with T-PIGN is proposed. Finally, the applicability of the proposed method is verified by concrete examples.

Weapons system portfolio selection based on the contribution rate evaluation of system of systems

The weapons system portfolio selection problem arises at the equipment demonstration stage and deals with the military application requirements.Further,the contribution rate of the system is one of the important indicators to evaluate the role of a system,which can facilitate the weapons system portfolio selection.Therefore,combining the system contribution rate with system portfolio selection is the focus of this study.It also focuses on calculating the contribution rates of multiple equipment systems with various types of capabilities.The contribution rate is measured by establishing a hierarchical multi-criteria value model from three dimensions.Based on the value model,the feasible portfolios are developed under certain cost constraints and the optimal weapons system portfolios are obtained by using the classification optimization selection strategy.Finally,an illustrative example is presented to verify the feasibility of the proposed model.

Evaluation and Selection of Introduced Tree Species in the Beijing-Tianjin Corridor

Based on the extensive analysis of natural and social conditions,regional development,and characteristics of tree species in the Beijing-Tianjin corridor,a comprehensive evaluation index system that consists of A,B,C,D layers was established for introduced tree species.Nine local representative introduced tree species were evaluated using the analytic hierarchy process(AHP).The results showed that Platanus orientalis,Quercus mongolicus,and Zizyphusjujube performed better comprehensively and were recommended as the dominant introduced tree species in the Beijing-Tianjin corridor.Other representative introduced tree species should be appropriately developed in the region.Main factors that should be taken into account for introduced tree species including drought tolerance,wintering habit,growth rate,leanness tolerance,pollution tolerance,saline tolerance,and disease resistance.

Selection and evaluation of suitable tree species in dry and dusty mining areas of Northwest China

To select drought-resistant and dust-tolerant native species suitable for use in the rehabilitation of major coal bases in northwest China,nine tree species were identified for growth rates,biomass,harm index,and physiological indices under drought and high dust stress conditions.The results showed that,in the dust resistance index system,the order was Caragana korshinskii>Amorpha fruticosa>Sabina vulgaris>Hedysarum scoparium>Tamarix chinensis>Ammopiptanthus mongolicus>Ulmus pumila>C aryopteris mongholica>Elaeagnus angustifolia.In a comprehensive drought and dust resistance index system,14 indices(such as shoot length,stomatal conductance,and peroxidase)had the larger weight indices.The drought and dust resistance order of the tree species was C aragana korshinskii>Ulmus pumila>Amorpha fruticosa>Sabina vulgaris>Caryopteris mongholica>Ammopiptanthus mongolicus>H edysarum scoparium>Tamarix chinensis>Elaeagnus angustifolia.This study provides effective strategies and references for selecting suitable tree species for arid mining sites in China,and also for the revegetation of coal mining sites worldwide.

Reliability Evaluation Optimal Selection Model of Component-Based System

If the components in a component-based software system come from different sources, the characteristics of the components may be different. Therefore, evaluating the reliability of a component-based system with a fixed model for all components will not be reasonable. To solve this problem, this paper combines a single reliability growth model with an architecture-based reliability model, and proposes an optimal selecting approach. First, the most appropriate model of each component is selected according to the historical reliability data of the component, so that the evaluation deviation is the smallest. Then, system reliability is evaluated according to both the relationships among components and the using frequency of each component. As the approach takes into account the historical data and the using frequency of each component, the evaluation and prediction results are more accurate than those of using a single model.

Evaluation of Feature Subset Selection, Feature Weighting, and Prototype Selection for Biomedical Applications

Many medical diagnosis applications are characterized by datasets that contain under-represented classes due to the fact that the disease is much rarer than the normal case. In such a situation classifiers such as decision trees and Na?ve Bayesian that generalize over the data are not the proper choice as classification methods. Case-based classifiers that can work on the samples seen so far are more appropriate for such a task. We propose to calculate the contingency table and class specific evaluation measures despite the overall accuracy for evaluation purposes of classifiers for these specific data characteristics. We evaluate the different options of our case-based classifier and compare the perform-ance to decision trees and Na?ve Bayesian. Finally, we give an outlook for further work.

A Weighted Combination Forecasting Model for Power Load Based on Forecasting Model Selection and Fuzzy Scale Joint Evaluation

To solve the medium and long term power load forecasting problem,the combination forecasting method is further expanded and a weighted combination forecasting model for power load is put forward.This model is divided into two stages which are forecasting model selection and weighted combination forecasting.Based on Markov chain conversion and cloud model,the forecasting model selection is implanted and several outstanding models are selected for the combination forecasting.For the weighted combination forecasting,a fuzzy scale joint evaluation method is proposed to determine the weight of selected forecasting model.The percentage error and mean absolute percentage error of weighted combination forecasting result of the power consumption in a certain area of China are 0.7439%and 0.3198%,respectively,while the maximum values of these two indexes of single forecasting models are 5.2278%and 1.9497%.It shows that the forecasting indexes of proposed model are improved significantly compared with the single forecasting models.

Evaluation and selection of the ship collaborative design resources based on AHP and genetic and simulated annealing algorithm

The characteristics of the design resources in the ship collaborative design is described and the hierarchical model for the evaluation of the design resources is established. The comprehensive evaluation of the co-designers for the collaborative design resources has been done from different aspects using Analytic Hierarchy Process (AHP),and according to the evaluation results,the candidates are determined. Meanwhile,based on the principle of minimum cost,and starting from the relations between the design tasks and the corresponding co-designers,the optimizing selection model of the collaborators is established and one novel genetic combined with simulated annealing algorithm is proposed to realize the optimization. It overcomes the defects of the genetic algorithm which may lead to the premature convergence and local optimization if used individually. Through the application of this method in the ship collaborative design system,it proves the feasibility and provides a quantitative method for the optimizing selection of the design resources.

EXPERIMENTAL STUDIES OF MEDICAL EQUIPMENT SELECTION BY USING THE MULTI-STAGE WEIGHTING EVALUATION METHOD

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Site Selection of Land Consolidation Project Based on Farmland Quality Evaluation in Yanjin County of Henan Province

In order to explore the effects of farmland quality evaluation on site selection of land consolidation projects,the methods of agricultural land use classification were used. Taking several project areas in Yanjin County of Henan Province as examples,the farmland quality before and after land consolidation projects was evaluated. The results indicate that under the conditions of reasonable site selection,the implementation of land consolidation projects can effectively improve the farmland quality and increase the grain productivity. Therefore,before the site selection for land consolidation projects,it is recommended to carry out pre-evaluation of farmland quality,and guide the project implementation according to the evaluation results. Besides,it is recommended to focus on medium and low level farmland with large centralized area,excellent original production conditions,but low level of development and use.

High-quality development level evaluation and path selection of prefabricated buildings

For a long time,Chinese construction industry has had disadvantages such as waste of resources,environmental pollution,long construction period,great influence by weather,low enterprise efficiency and poor benefit.While being able to solve the disadvantages of traditional buildings,prefabricated buildings,as an important starting point to achieve the carbon peaking and carbon neutrality goals,are far superior to traditional buildings in green and low-carbon,energy conservation and emission reduction,which can accelerate the transformation and upgrading of the construction industry.In recent years,the government has vigorously promoted prefabricated buildings,but the implementation of prefabricated buildings has been frequently hindered and the development of prefabricated buildings in China has not achieve the expected goal in many aspects.Under the high-quality development strategy proposed by the central government,how to promote the high-quality development of prefabricated buildings in China is one of the key difficulties of Chinese construction industry in the future.Therefore,it is necessary to proceed from the connotation of the high-quality development of prefabricated buildings,establish an evaluation model for the high-quality development level of prefabricated buildings through AHP and comprehensive fuzzy evaluation to master the high-quality development level of prefabricated buildings in China,and explore the reasonable paths selection forthe high-quality development of prefabricated buildings in China.

Modified Adhoc On-Demand Distance Vector for Trust Evaluation And Attack Detection

Recently,Wireless Sensor Network(WSN)becomes most potential technologies for providing improved services to several data gathering and track-ing applications.Because of the wireless medium,multi-hop communication,absence of physical protectivity,and accumulated traffic,WSN is highly vulner-able to security concerns.Therefore,this study explores a specific type of DoS attack identified as a selective forwarding attack where the misbehaving node in the network drops packet on a selective basis.It is challenging to determine if packet loss is caused by a collision in the medium access path,poor channel quality,or a selective forwarding assault.Identifying misbehaving nodes at the earliest opportunity is an acceptable solution for performing secure routing in such networks.As a result,in this study effort,we present a unique Modified Ad Hoc On-Demand Distance Vector(AODV)Routing protocol depending upon the One time password(OTP)method that employs the RSA algorithm.Finally,a trust evaluation process determines which approach is the most optimal.Accord-ing to the simulationfindings of the suggested routing protocol and comparison with existing routing protocols provided in this article,the proposed work is both efficient and cost-effective.

Probe Selection for Over-the-Air Test in 5G Base Stations with Massive Multiple-Input Multiple-Output

In 5G systems, massive multiple-input multiple-output (MIMO) has been adopted in base stations (BSs) to improve spectral efficiency and coverage. The traditional conductive performance test techniques are challenging due to the unaffordable cost and high complexity when testing a large number of antennas. To solve this problem, the over-the-air (OTA) test has been presented, in which probe selection is the key to reduce the number of channel emulators and probes. In this paper, a novel artificial bee colony (ABC) algorithm is introduced to enhance the efficiency and accuracy of probe selection procedure. A sectoring- based multi-probe anechoic chamber (MPAC) is built to evaluate the throughput performance of massive MIMO equipped in 5G BS. In addition, link level simulation is carried out to evaluate the proposal’s performance gain under the commercial network assumptions, where the average throughput of three velocity is given with different SNR region. The results suggest that OTA chamber and multi-probe wall are available not only for 5G BSs, but also for user equipments (UEs) with end-to-end communication.

WEB SERVICE SELECTION ALGORITHM BASED ON PRINCIPAL COMPONENT ANALYSIS

Existing Web service selection approaches usually assume that preferences of users have been provided in a quantitative form by users. However, due to the subjectivity and vagueness of preferences, it may be impractical for users to specify quantitative and exact preferences. Moreover, due to that Quality of Service (QoS) attributes are often interrelated, existing Web service selection approaches which employ weighted summation of QoS attribute values to compute the overall QoS of Web services may produce inaccurate results, since they do not take correlations among QoS attributes into account. To resolve these problems, a Web service selection framework considering user's preference priority is proposed, which incorporates a searching mechanism with QoS range setting to identify services satisfying the user's QoS constraints. With the identified service candidates, based on the idea of Principal Component Analysis (PCA), an algorithm of Web service selection named PCA-WSS (Web Service Selection based on PCA) is proposed, which can eliminate the correlations among QoS attributes and compute the overall QoS of Web services accurately. After computing the overall QoS for each service, the algorithm ranks the Web service candidates based on their overall QoS and recommends services with top QoS values to users. Finally, the effectiveness and feasibility of our approach are validated by experiments, i.e. the selected Web service by our approach is given high average evaluation than other ones by users and the time cost of PCA-WSS algorithm is not affected acutely by the number of service candidates.

Logistic and SVM Credit Score Models Based on Lasso Variable Selection

There are many factors influencing personal credit. We introduce Lasso technique to personal credit evaluation, and establish Lasso-logistic, Lasso-SVM and Group lasso-logistic models respectively. Variable selection and parameter estimation are also conducted simultaneously. Based on the personal credit data set from a certain lending platform, it can be concluded through experiments that compared with the full-variable Logistic model and the stepwise Logistic model, the variable selection ability of Group lasso-logistic model was the strongest, followed by Lasso-logistic and Lasso-SVM respectively. All three models based on Lasso variable selection have better filtering capability than stepwise selection. In the meantime, the Group lasso-logistic model can eliminate or retain relevant virtual variables as a group to facilitate model interpretation. In terms of prediction accuracy, Lasso-SVM had the highest prediction accuracy for default users in the training set, while in the test set, Group lasso-logistic had the best classification accuracy for default users. Whether in the training set or in the test set, the Lasso-logistic model has the best classification accuracy for non-default users. The model based on Lasso variable selection can also better screen out the key factors influencing personal credit risk.

Credit risk evaluation using adaptive Lq penalty SVM with Gauss kernel

In order to improve the performance of support vector machine (SVM) applications in the field of credit risk evaluation, an adaptive Lq SVM model with Gauss kernel (ALqG-SVM) is proposed to evaluate credit risks. The non-adaptive penalty of the object function is extended to (0, 2] to increase classification accuracy. To further improve the generalization performance of the proposed model, the Gauss kernel is introduced, thus the non-linear classification problem can be linearly separated in higher dimensional feature space. Two UCI credit datasets and a real life credit dataset from a US major commercial bank are used to check the efficiency of this model. Compared with other popular methods, satisfactory results are obtained through a novel method in the area of credit risk evaluation. So the new model is an excellent choice.