Whitenization Weight Function Research Articles

Analysis of Enterprise Financial Risk Early Warning Model Based on the Evidence Theory and Whitening Weight Function

Analysis of Enterprise Financial Risk Early Warning Model Based on the Evidence Theory and Whitening Weight Function

Application of information fusion technology to build knowledge service model of university smart archives

Abstract Based on the SERVQUAL evaluation model, this paper examines the characteristics and service model of university archive services and establishes a knowledge service model framework for university smart archives. The service framework utilizes information fusion technology to quantitatively analyze the archive situation through the combination of 6 dimensions and 23 secondary indicators. One of the key points is to combine the whitening weight function of upper and lower limit measurements and the central whitening weight function to form a grey clustering algorithm in order to solve the “cliff” effect of the whitening weight function of the traditional upper and lower limit measurements. After the development of the system was completed, the index weights were first calculated by means of a questionnaire and then practiced in the school. The results show that responsiveness has the highest weight, 0.8612; security is second, 0.6321. And tangibility is the last, only 0.1792. The first college scored 0.461 in C1, and the second college scored only 1.87 in E1, which pulled the average score of the first-level index to 4.52. After the practice, the survey proved that the system meets the needs of the college and can point out areas for archive improvement. Archives improvement direction.

Evaluation of county-level integrated health organizations: Combination of the weighting-grey synthetic evaluation method

This paper aims to improve the efficacy assessment of County-level Integrated Health Organizations (CIHOs) in China. By analyzing CIHOs in Fujian Province, an empirical study was done to confirm the efficacy of the combined weighted-grey synthetic evaluation approach. The combined weights of evaluation indicators are calculated using the suggested method, which combines the analytical network process method and the coefficient of variation method. The grey center points of the CIHOs to be evaluated are determined, the whitenization weight functions is constructed, a comprehensive evaluation matrix is established, and then the composite score values are calculated and ranked. A more thorough evaluation of CIHOs can be accomplished scientifically using this comprehensive approach.

Grey Systems Model to Assess Water Quality in Mantaro River in Peru

The section of the Mantaro River that flows through the department of Huancavelica, Peru, has been affected by toxic wastes and mineral residues from industrial and mining activities, which have directly impacted the water quality. In this work, a grey system model, based on the grey clustering method, was used to assess water quality. The grey clustering method was applied using the central point of triangular whitening weight functions (CTWF). In addition, the Prati index and the Environmental Quality Standards for water from the Peru government were revised and used for this study. In the case study, six physicochemical parameters, pH, DO, BOD, Cd, As, and Pb, at nine monitoring points were assessed along the Mantaro River. The results showed that the sixth monitoring point (P6), which is influenced by mining activity, was highly contaminated, while the other points were classified as noncontaminated. Finally, the results obtained by applying the grey clustering method can be useful to competent authorities, for decision making on water management in this watershed.

Research on New Liberal Arts Professional Talent Cultivation Model Based on OBE Concept

Abstract In this paper, an evaluation model is constructed to evaluate the new talent cultivation model of liberal arts under the OBE concept by analyzing the steps and ways of the model. The system of talent cultivation is determined by establishing the sample value and the whitening weight function of the gray class, and the system indicators are represented using the gray clustering weights, clustering coefficients, and clustering vectors. Then the system indexes are processed, and a multi-level DEA model is introduced on the basis of the gray clustering talent cultivation evaluation system. Finally, the multi-level gray clustering talent cultivation comprehensive evaluation model was constructed. The evaluation of the talent cultivation model is B=(0.4, 0.51, 0.09, 0, 0), and the overall evaluation result of the talent cultivation model is “excellent” according to the principle of maximum affiliation according to the calculation results.

A study of investment decision behavior based on risk analysis

Abstract Risk analysis of investment decision-making behavior is to improve the ability to prevent investment risks in order to guarantee the success rate of investment decisions. In this paper, the risk evaluation level is determined by calculating the correlation degree of risk indicators through the establishment of the material topology matrix, and the gray evaluation coefficients are determined by using the gray correlation analysis of the whitening weight function to construct the gray evaluation model. The risk index factors and the overall gray evaluation were analyzed by using the material topology model and the gray evaluation model. From the physical topology evaluation, the market risk correlation is −0.00825, which means the special level risk. From the grey comprehensive evaluation score, the overall evaluation score is 6.884 overall risk level is medium grade line. This shows that using the model constructed in this paper can effectively realize the risk analysis of investment decisions and provide a guidance basis for investors to take effective measures for different types of risks.

A Novel Method of Teaching Quality Monitoring and Evaluation from the Perspective of Educational Balance

Exploring the problem of teaching quality monitoring and evaluation from the perspective of educational balance can help educators and policy makers discover educational inequality problems, thereby promoting fair allocation of educational resources and opportunities. In light of this, this study attempts to research teaching quality monitoring and evaluation from the perspective of educational balance. At first, the mechanism of promoting educational balance by information technology was expounded, and the principle and necessity of a comprehensive assessment based on the evaluation results of different evaluators were explained. Then, this study innovatively introduced the whitening weight function (WWF)-grey evaluation model into the conventional grey clustering evaluation, calculated the unit comprehensive clustering coefficients of the indexes of teaching quality evaluation from the perspective of educational balance, and gave fair, accurate, and effective evaluations. After that, the grey GM (1,1) model was applied to the prediction of teaching quality improvement effect, the future trend of teaching quality changes was predicted based on history data, and the results provided references for teaching reform and educational decision-making. At last, experimental results verified the validity of the proposed method.

Industrial ecological evaluation based on DPSIR and panel grey clustering model

PurposeThis paper aims to build an improved grey panel clustering evaluation model and evaluate the comprehensive development potential of industrial economy, society and ecological environment in the Yangtze River Economic Belt of China. The purpose of this study is to provide some theoretical basis and tool support for management departments and relevant researchers engaged in industrial sustainable development.Design/methodology/approachThis study uses the driving force pressure state impact response analysis framework to build a comprehensive evaluation index system. Based on the center point triangle whitening weight function, it classifies the panel grey clustering of improvement time and index weight.FindingsThe results show that there are great differences in the level of industrial ecological development in different regions of the Yangtze River Economic Belt, which further illustrates the scientificity and rationality of the evaluation method proposed in this paper.Practical implicationsDue to the industrial ecological development is in a constantly changing state, and the information is uncertain. Whitening weight function is introduced to represent the complete information of relevant data. The industrial ecological evaluation involves a comprehensive complex system, which belongs to the panel data analysis problem. The improved grey panel clustering evaluation model is applied to grade the industrial ecological development level of the Yangtze River Economic Belt. The results have important guiding significance for the balanced development of industrial ecology in the region.Social implicationsDue to the industrial ecological development is in a constantly changing state, and the information is uncertain. Whitening weight function is introduced to represent the complete information of relevant data. The industrial ecological evaluation involves a comprehensive complex system, which belongs to the panel data analysis problem. In order to improve the effectiveness of industrial ecological evaluation, the improved grey panel clustering evaluation model is applied to grade the industrial ecological development level of the Yangtze River Economic Belt. The results have important guiding significance for the balanced development of industrial ecology in the region.Originality/valuethe new model proposed in this paper complements and improves the grey clustering analysis theory of panel data, that is, aiming at the subjective limitation of using time degree to determine time weight in panel grey clustering, a comprehensive theoretical method for determining time weight is creatively proposed. Combining the DPSIR (Driving force-Pressure-State-Influence-Response) model model with ecological development, a comprehensive evaluation model is constructed to make the evaluation results more authentic and comprehensive.

Selection of Logistics Service Provider for port enterprises: Combination of the weighting-grey synthetic decision-making method

The purpose of this paper is to explore how port enterprises can scientifically select a better logistic service provider (LSP) to achieve a high efficiency. An empirical study is conducted to verify the effectiveness of the combination weighting-grey synthetic decision-making method by helping the LSP selection of a port enterprise in China. Data are collected from questionnaires administered to port logistics’ industry professionals. The method is proposed, which associates the analysis network process method with the entropy method to determine the combined weights of the evaluation indexes. The improved centre-point triangular whitenization weight function is introduced to cluster the alternative port LSPs and judge the corresponding grey classes. Subsequently, the synthetic weighted decision-making vectors are used to determine the grey synthetic decision-making coefficient vectors. The grey synthetic clustering decision-making coefficients are calculated to establish a synthetic decision-making rank of the alternative plans. The combined method can help the port enterprises realize the selection of better LSPs in a scientific manner.

GCA-CNN based transformer digital twin model construction and fault diagnosis and condition evaluation analysis

Oil-immersed power transformer is the most important piece of equipment in the transmission system, and the stable operation of this equipment is of great significance to the normal work of the power system. At present, deep learning has been widely used in transformer condition evaluation and fault detection. About the shortage of deep learning algorithm models, this paper proposes a transformer digital twin model construction and fault diagnosis and condition evaluation analysis based on gray clustering algorithm (GCA) and conventional neural network (CNN). The data are first collected and filtered by combining the operation data, condition information amount and faulty features of power transformers, and then the condition features and fault features are combined to evaluate and detect the condition and faults of power transformers using GCA-CNN respectively. The whitening weight function is determined by expert scoring, the state evaluation matrix is established, the evaluation coefficients are obtained to calculate the evaluation weights, and the transformer state is obtained according to the clustering coefficients; 2000 pieces of raw data are input into the model to obtain the output fault types. Finally, the results are derived and compared with the real results. This paper uses real data from a power plant in Yunnan, and according to the results, the model established in this paper has higher accuracy and better evaluation and detection effects.

Retraction Note: A Post-Evaluation Method for Integrated Energy Systems Based on Triangular Whitening Weight Function

The authors have expressed the wish to retract this article on the ground that there are some technical issues that require to be corrected. 1. The indicator does not provide a specific quantification method. 2. The indicator weight is obtained through subjective evaluation where there is a significant deviation between the actual project verification and the current comprehensive energy system operation results. 3. The post evaluation index values in the article are only obtained based on the average value obtained from expert scoring, and the fitting results do not have reference significance. The Publisher and Editor(s) approved to the retraction.

A Post-Evaluation Method for Integrated Energy Systems Based on Triangular Whitening Weight Function

Aiming at the problems of incomplete post evaluation system and incomplete evaluation perspective for integrated energy systems, a relatively overall post evaluation system for integrated energy systems was constructed, with indicators covering six aspects: economy, energy utilization, environmental protection, safety and reliability, the entire process of the project, and social impact. Based on this, an analytic hierarchy process (AHP) and a post-evaluation method for integrated energy systems based on triangular whitening weight function was proposed to scientifically provide comprehensive results of integrated energy post evaluation.

How to determinate water quality using an artificial intelligent model based on grey clustering?

Water quality is an important topic for countries like Peru, where the mining sector is one of the main economic activities, so the study of its impact on water quality is also necessary to have a regular control of benefits and dangers. In this way, to achieve this objective, the chosen methodology was grey clustering, which is based on artificial intelligent theory. Specifically, the central point triangular whitening weight function better known as CTWF, which is an approach from grey clustering, was used. The case study was focused on the Mashcon and Chonta rivers, located in the province of Cajamarca, Peru, these rivers are directly affected by an open pit mine. The study was carried out taking into account thirteen monitoring points taken by National Water Authority (ANA). The results showed that all the points considered were classified as not contaminated, A1 category, this using the parameters of the Peruvian government. With these results, the mining company was able to demonstrate that they are taking the water quality into account and that they are making an effort to keep these rivers as healthy as possible.

An Intelligent Gray Prediction Model Based on Fuzzy Theory

In order to improve the forecasting effect of the gray prediction model, this paper combines the fuzzy theory to construct the gray prediction model and explores its forecasting accuracy. Moreover, this paper uses the entropy weight method to obtain the objective weight to correct the subjective weight, which makes the weight calculation more reasonable. In view of the uncertainty of the control signal of the research object, this paper introduces the gray system theory to conduct cluster analysis on the fire control computer and mainly introduces the general whitening weight function. Furthermore, this paper adopts the center point mixed with a triangular whitening weight function to carry out gray clustering according to the difficulty of defining the gray class boundary and gives the solution steps to obtain the intelligent gray prediction model. Finally, this paper verifies that the intelligent gray prediction model based on fuzzy theory has a good effect through experiments, which can effectively improve the prediction effect of the intelligent prediction model.

Applying Grey Clustering Method and Pearson Correlation to Assess Water Quality

The Mantaro River travels through Junín, Ayacucho, and Huancavelica departments,in Peru, and receives not only domestic discharges from the population but also tailings fields and dumps containing lead, silver, copper, and zinc from mining companies. To be able to assess the water quality, the grey clustering method was applied, using Center-point Triangular Whitenization Weight Functions (CTWF) for this purpose. As well, Pearson correlation between parameters was used to understand the dynamics of pollution. In the watershed of the Mantaro river the results of the Monitoring of the Surface Water published in 2018 by the Mantaro Water Administrative Authority were compared to the Peruvian Environmental Quality Standards (ECA) Category 1, subcategory A parameters. The results obtained suggest that the main driver of pollution in the Mantaro river is not mining, but domestic waste in landfills and probably agriculture. Finally, this study shows responsible environmental management by mining companies, besides, could be helpful for regional and local authorities of Peru in making decisions to improve the management of the Mantaro river watershed and make the population aware of the sustainable use of water

The Evaluation Method of Community Emergency Resource Allocation Based on Coordination Sensor Information Collection

This paper analyzes the information collection data of coordination sensors and designs a corresponding evaluation method to conduct an in-depth assessment of the configuration of community emergency resources. Based on the principles of assessment index system construction and the actual research, an assessment index system of community emergency resource allocation level is established. In this paper, the G1 method was selected to determine the weights of the evaluation indexes, and the gray clustering method was applied to construct the whitening weight function, determine the gray level to which each index belongs and the affiliation degree of each gray class, and establish a comprehensive evaluation model of the community emergency resource allocation level. In response to the problem that the increase of state variables leads to a decrease in real-time map building, a dynamic local window size mechanism is proposed, which can reduce the time consumption and save computational resources under the condition of ensuring the accuracy of positioning and map building. Therefore, it is urgent to design an efficient self-interference cancellation mechanism to resist the influence of self-interference on the signal-to-noise ratio of the first-hop link. For example, the IMU pre integration theory is combined with the wheel range method to solve the problem of frequency synchronization; An initialization algorithm is proposed to recover the scale information of the camera and optimize the external parameters; Design a graphic optimization framework integrating IMU, wheel range finder and camera. The monitoring terminal sends the data information of coordination transportation to the monitoring platform in real-time, and the monitoring platform is responsible for storing and displaying the data information, thus realizing the real-time monitoring of the coordination transportation process. Finally, the functions of the monitoring terminal and the display system of the monitoring platform experiment, respectively, and the test results verify the effectiveness and integrity of the system data communication, which proves the correctness of the terminal design of the integrated coordination monitoring system based on multidimensional information and has practical engineering value.

Multiobjective Optimization Design of Green Building Energy Consumption Based on Inorganic Thermal Insulation Nanomaterials.

In order to solve the problem that building engineering construction needs to consume a lot of energy and cause environmental pollution, which will pose a great pressure on urban resources and environment, this paper proposes that, in building engineering construction, appropriate green construction technology must be selected in combination with the actual situation, so as to effectively reduce the energy consumption of building engineering and improve the use efficiency of building engineering. Firstly, good thermal insulation nanomaterials are selected, which are cost-effective, safe, and nontoxic and has small thermal conductivity, large heat storage coefficient, stable chemical performance, and good construction performance. Secondly, it also needs to be selected according to the actual service life of the building. Because the current evaluation system is mostly aimed at the planning and design stage, and the structure occupies a large part in the building, for example, the impact on the construction period accounts for more than 50% and the impact on the cost accounts for 35%. Therefore, Duan Xiaorong and others established the grey cluster evaluation model of green building structure design based on the triangular whitening weight function. Finally, according to the relevant national regulations, this paper optimizes the design of green buildings based on the basic principles of energy conservation and emission reduction, high quality, and high efficiency.

Grey Clustering Evaluation of Prefabricated Building Construction Safety Based on Anp

Starting from the four common types of safety accidents at the construction site of prefabricated buildings, the theory of cause of accidents is used to discover the main causes of accidents, and the construction safety evaluation indicators are extracted from them and the safety risk evaluation index system is constructed. Then combined with the application of network level analysis and mixed central point triangle whitening weight function to build a model that can evaluate the safety risk of prefabricated building construction. Finally, the model is tested with examples, and factors in an unsafe state are identified and suggestions are made. Provide models and references for the safety management of prefabricated construction sites, thereby reducing safety accidents on the construction site.

Evaluation method of building decoration engineering based on interactive information model

In order to improve the accuracy of architectural decoration engineering evaluation, a new evaluation method based on interactive information model is proposed in this paper. First, the paper establishes iim model to complete the evaluation index system of architectural decoration engineering. Then, the weight vectors of the criterion layer and the target layer are determined by the mathematical analytic hierarchy process. Finally, the comprehensive evaluation result of low-carbon Green building design scheme is obtained by calculating the whitening weight function of each gray class. The experimental results show that the method has high accuracy and strong practicability.

Port Capability Evaluation from the Perspective of Supply Chain

Today’s ports have become an important node in the global supply chain. It is particularly important to make a scientific assessment of the comprehensive capabilities of the port and to provide a reference for the long-term development of the port. From the perspective of the supply chain, this article first selects the evaluation indicators that affect the port’s capabilities from four aspects of port resource ownership, control management, comprehensive services, and innovation-driven aspect. Secondly, we use the expert scoring method to judge the importance of the evaluation indicators and build a scientific and independent port capacity evaluation system from the perspective of the supply chain. Then, this paper uses the analytic hierarchy process to determine the weight coefficients of each evaluation index and uses the gray cluster analysis method of the triangular whitening weight function based on the center point to establish a qualitative and quantitative port capacity evaluation model from the perspective of the supply chain. Finally, we take a port in Northeast Asia as an example to conduct an empirical analysis to verify the feasibility of the port capacity evaluation system and model from the perspective of the supply chain constructed in this paper. The research results of this article can well analyze the port’s resource ownership, control and management capabilities, comprehensive service capabilities, and innovation-driven capabilities and provide a practical and effective theoretical basis for the port’s key development directions.