Comparative Evaluation of Predicting Energy Consumption of Absorption Heat Pump with Multilayer Shallow Neural Network Training Algorithms

The performance of various multilayer neural network algorithms to predict the energy consumption of an absorption chiller in an air conditioning system under the same conditions was compared and evaluated in this study. Each prediction model was created using 12 representative multilayer shallow neural network algorithms. As training data, about a month of actual operation data during the heating period was used, and the predictive performance of 12 algorithms according to the training size was evaluated. The prediction results indicate that the error rates using the measured values are 0.09% minimum, 5.76% maximum, and 1.94 standard deviation (SD) for the Levenberg–Marquardt backpropagation model and 0.41% minimum, 5.05% maximum, and 1.68 SD for the Bayesian regularization backpropagation model. The conjugate gradient with Polak–Ribiére updates backpropagation model yielded lower values than the other two models, with 0.31% minimum, 5.73% maximum, and 1.76 SD. Based on the results for the predictive performance evaluation index, CvRMSE, all other models (conjugate gradient with Fletcher–Reeves updates backpropagation, one-step secant backpropagation, gradient descent with momentum and adaptive learning rate backpropagation, gradient descent with momentum backpropagation) except for the gradient descent backpropagation model yielded results that satisfy ASHRAE (American Society of Heating, Refrigerating and Air-Conditioning Engineers) Guideline 14. The results of this study confirm that the prediction performance may differ for each multilayer neural network training algorithm. Therefore, selecting the appropriate model to fit the characteristics of a specific project is essential.

Contribution Modeling on Condition Evaluation of Asphalt Pavement Using Uncertainty Measurement and Entropy Theory

In view of the deficiency that traditional pavement performance evaluation index did not consider the influence of their difference on weight, the grade of the evaluation index also did not take into account intermediate state and the impact of uncertainty on the evaluation results, a determination method of pavement performance evaluation index weight based on entropy theory was developed. The unascertained measurement function of evaluation index was performed by left-half ladder distribution, and unascertained measurement matrix was obtained. The index weight was calculated by minimum entropy theory, and the practicability of this method was verified through a concrete example finally. The results show that there were different weights in different samples, which depended on index measurement function and were the overall characterization of comprehensive measurement of every index. The method which is based on the given weighting factor did not conform to the engineering facts. It was difficult to identify the importance of the pavement performance evaluation index in different samples. The balance of the various indexes is better to be considered in the proposed method, and the comprehensive situation of pavement performance is really reflected, which improves the evaluation of the reliability.

Performance Evaluation Model of Public Resource Trading Platform Using Entropy-Based Gray Clustering Method

In order to standardize public resource trading activities and improve the operating efficiency of public resource trading platforms, this paper conducts research on the performance of public resource trading platforms. A three-level and 28-dimension performance evaluation index system for public resource trading platform is established by considering the four levels of “input-process-output-effect.” Besides, entropy weight method, gray clustering, and fuzzy comprehensive evaluation are integrated on this basis. Entropy weight method is used to determine the index weight, and the degree value of membership for indexes on gray class is determined based on gray clustering method and converted into a matrix. Then, fuzzy comprehensive evaluation method is used to determine the evaluation value and finally carry out the platform performance evaluation, which provides theoretical support for academic researchers to conduct follow-up research on the performance evaluation of public resource trading platforms.

The Evaluation of Synergy between University Entrepreneurship Education Ecosystem and University Students’ Entrepreneurship Performance

The interactive mechanism between college and university entrepreneurship education ecosystem and their students’ entrepreneurial performance needs to be further discussed, as college and university students are an important force in entrepreneurship. Since there is a lack of symbiotic mechanism analysis and interactive optimization research using ecological methods, this paper constructs the evaluation index system of entrepreneurship education ecosystem and entrepreneurship performance evaluation index system and uses the entropy weight method to determine the weight of various indicators in the index system more objectively. In this paper, Lotka–Volterra model in ecology is used to deeply study the mechanism between college and university entrepreneurship education ecosystem and entrepreneurship performance. Lotka–Volterra multichoice goal programming (MCGP) model is used to optimize the collaborative relationship between college and university entrepreneurship education ecosystem and entrepreneurship performance. Finally, a numerical example is given to illustrate the feasibility and effectiveness of the research method. The results show that Lotka–Volterra multichoice goal programming (MCGP) method is effective in evaluating the synergy between college and university entrepreneurship education ecosystem and the students’ entrepreneurship performance.

Model and algorithm of innovation performance evaluation for coordination of supply and demand based on wireless sensor network

In recent years, with the continuous development and progress of wireless communication and sensors, people's production and life have also undergone tremendous changes. This article aims to apply wireless sensor networks to the construction of a supply–demand coordination innovation performance evaluation model, in order to improve its influence and application scope in real life. This paper deeply researches the architecture and node organization structure of wireless sensor network, and strengthens its theoretical foundation in the application of performance evaluation model. This paper designs performance evaluation indicators and compares performance evaluation methods at home and abroad based on the evaluation indicators, compares and analyzes the factor analysis method, fuzzy comprehensive evaluation method, comprehensive index evaluation method, etc., draws the advantages and disadvantages of each method, and uses them reasonably. The performance evaluation model constructed in this paper adopts the production function method and the analytic hierarchy process. According to the principles of scientificity, feasibility, and economy, the performance indicators for evaluating the balance of supply and demand are screened out, and score evaluation and comparison of each indicator are carried out. Finally, this paper analyzes the corporate performance evaluation index composition, model regression, sensor performance and performance evaluation scores, etc., and has a comprehensive application analysis of the model constructed in this paper. As can be seen from the overall score we selected five companies, enterprises composite score is 83.574, ranking first, followed by a score of 78.421.

Tobacco Enterprise Logistics Performance Evaluation Based on Principal Component Analysis

Objectives: Tobacco logistics matters greatly in the development of the tobacco industry. Logistics performance evaluation is a sub-part of tobacco enterprise management performance evaluation. The in-depth study of logistics performance evaluation can form a more comprehensive enterprise management performance evaluation system, and provide logistics management tools such as control, diagnosis and coordination for enterprise logistics management. Methods: In this paper, a tobacco enterprise logistics performance evaluation index system is constructed from six aspects, including transportation, warehousing, inventory management, informatization, customer service and finance. A tobacco enterprise logistics performance evaluation method based on principal component analysis is put forward. Results: Through calculation, the comprehensive evaluation value of tobacco logistics performance of enterprises X in each year is obtained. The enterprise logistics performance is the worst in 2016. The enterprise logistics performance is the best in 2019. It indicates that the logistics level and ability of tobacco enterprises are improving year by year. Conclusion: Seen from the example, the principal component analysis method can be used to properly evaluate the logistics performance level of tobacco enterprises, and provide objective and quantitative reference data for tobacco enterprises to improve their logistics performance level and benefits.

Evaluation Method for Winding Performance of Distribution Transformer

In order to ensure the safe and stable operation of a power system, the performance evaluation of transformer windings after a short-circuit test can predict whether the windings are deformed in order to provide a useful reference for the operation and maintenance of the power sector. This paper proposes a method for evaluating the performance of transformer windings in order to improve the overall effectiveness of a winding evaluation. The index data obtained based on a short-circuit impedance method, frequency response method, and oscillation wave method are used in the algorithm proposed in this paper. First, the transformer winding performance evaluation index system is constructed. Second, the weight of each index is determined by analytic hierarchy process, and then the fuzzy comprehensive assessment method is introduced, and the fuzzy evaluation matrix is established, the evaluation results are calculated using the evaluation formula. Finally, the maximum membership principle is used to determine the performance level of the transformer winding on the evaluation results, and the evaluation results of the transformer winding state are obtained. The example shows that the evaluation level of the measured transformer winding performance can be obtained by this method as “good”. Compared with the traditional method, this method can simplify the evaluation while maintaining higher accuracy.

A best-worst-method-based performance evaluation framework for manufacturing industry

PurposeThe purpose of paper is to develop a performance evaluation framework for manufacturing industry to evaluate overall manufacturing performance.Design/methodology/approachThe best-worst method (BWM) is used to aid in developing a performance evaluation framework for manufacturing industry to evaluate their overall performance.FindingsThe proposed BWM-based manufacturing performance evaluation framework is implemented in an Indian steel manufacturing company to evaluate their overall manufacturing performance. Operational performance of the organization is very consistent and range between 60% and 70% throughout the year. Management performance can be seen high in the 1st and 2nd quarter of the financial year ranging from 70% to 80%, whereas a slight decrease in the management performance is observed in the 3rd and 4th quarter ranging from 60% to 70%. The social stakeholder performance has a peak in first quarter ranging from 80% to 100% as at start of financial year.Originality/valueThis paper utilized BWM, a MCDM method in developing a performance evaluation index that integrates several categories of manufacturing and evaluates overall manufacturing performance. This is a novel contribution to BWM decision-making application.