scholarly journals Study on an AHP-Entropy-ANFIS Model for the Prediction of the Unfrozen Water Content of Sodium-Bicarbonate-Type Salinization Frozen Soil

Mathematics ◽  
2020 ◽  
Vol 8 (8) ◽  
pp. 1209
Author(s):  
Qing Wang ◽  
Yufeng Liu ◽  
Xudong Zhang ◽  
Huicheng Fu ◽  
Sen Lin ◽  
...  
Keyword(s):  
Water Content ◽  
Frozen Soil ◽  
Support Vector ◽  
Unfrozen Water ◽  
Ensemble Model ◽  
Entropy Weight ◽  
Anfis Model ◽  
Inference System ◽  
Entropy Weight Method ◽  
Weight Method

The development of agriculture and ecology, and the construction of water conservancy facilities are seriously hindered by the salinization of seasonal frozen soil. Unfrozen water exists in the freezing and thawing of frozen soil. This unfrozen water is the core and foundation for studying the process of seasonal frozen soil salinization. However, it is difficult to obtain the unfrozen water content (UW) in routine experiments, and it shows nonlinear characteristics under the action of the main factors contained: salt content, water content, and temperature. In this paper, a new model is proposed to predict the UW of saline soil based on the combined weighting method and the adaptive neuro-fuzzy inference system (ANFIS). Firstly, the distance function was used to combine the analytic hierarchy process (AHP) with the entropy weight method (the combined weighting method) to determine the importance of the influencing factors (temperature, initial water content, and salt content) on UW. On this basis, the AHP, entropy weight method, and adaptive neuro-fuzzy inference system (AHP-entropy-ANFIS) ensemble model was established. Secondly, the five-fold cross-validation method and statistical factors (coefficient of determination, mean squared error, mean absolute percent error, and mean absolute error) were applied to evaluate and compare the AHP-entropy-ANFIS ensemble model, the ANFIS model, the support vector machine (SVM) model, and the AHP, entropy weight method, and support vector machine (AHP-entropy-SVM) ensemble model. In addition, the prediction values of the four models and the experimental values were also compared. The results show that the AHP-entropy-ANFIS model had the strongest prediction capability and the best stability, and so is more suitable for predicting the UW of saline soil. This study provides useful guidance for preventing and mitigating salinization hazards in seasonally frozen areas.

scholarly journals Using ANFIS and BPNN Methods to Predict the Unfrozen Water Content of Saline Soil in Western Jilin, China

Symmetry ◽  
2018 ◽  
Vol 11 (1) ◽  
pp. 16 ◽  
Author(s):  
Yufeng Liu ◽  
Qing Wang ◽  
Xudong Zhang ◽  
Shengyuan Song ◽  
Cencen Niu ◽  
...  
Keyword(s):  
Water Content ◽  
Saline Soil ◽  
Salt Content ◽  
Frozen Soil ◽  
Unfrozen Water ◽  
Initial Water Content ◽  
Initial Water ◽  
Inference System ◽  
Unfrozen Water Content ◽  
Western Jilin

: Saline soil in seasonally frozen soil areas has caused tremendous damage to engineering and the ecological environment. The unfrozen water is the main factor affecting the properties of saline soil in seasonally frozen soil area and therefore needs to be studied. However, due to the high cost of laboratory measurement of the unfrozen water content, this study focuses on using an adaptive network fuzzy inference system (ANFIS) and a back propagation neural network (BPNN) to predict the unfrozen water content of saline soil in the Zhenlai area, Western Jilin. The data for the constructed model is obtained by nuclear magnetic resonance (NMR) testing. The initial water content (W0), salt content (S), and temperature (T) are used as input parameters for predicting the unfrozen water content (Wu). The results of the ANFIS and BPNN models are compared. The results show that although both methods are suitable for predicting the unfrozen water content of saline soil in the Zhenlai area, western Jilin, the prediction accuracy of the ANFIS model is higher.

A fire risk assessment method based on the combination of quantified safety checklist and structure entropy weight for shopping malls

2021 ◽  
pp. 1748006X2098737
Author(s):  
Quanle Zou ◽  
Tiancheng Zhang ◽  
Wei Liu
Keyword(s):  
Evaluation Method ◽  
Research Result ◽  
Fire Risk ◽  
Living Standard ◽  
Shopping Malls ◽  
Entropy Weight ◽  
Essential Components ◽  
Entropy Weight Method ◽  
Weight Method ◽  
Laws And Regulations

In recent years, various large- and medium-sized shopping malls have been essential components of each city with the speed-up of China’s urbanization process and the improvement of residents’ living standard. A method for evaluating fire risk in shopping malls based on quantified safety checklist and structure entropy weight method was proposed according to related literatures as well as laws and regulations by analyzing the characteristics of fires occurring in shopping malls in recent years. At first, the factors influencing the fire risk in shopping malls were determined by carrying out on-site survey and visiting related organizations to construct an evaluation index system for fires occurring in shopping malls; afterwards, a quantified safety checklist composed of four parts (i.e. safety grade, grade description, scoring criterion and index quantification) was established based on related laws and regulations; subsequently, index weights were determined by utilizing structure entropy weight method, thus putting forward a method for assessing fire risk in shopping malls based on quantified safety checklist and structure entropy weight method. Eventually, the applicability of the evaluation method was validated exampled by Wal-Mart. The research result provides a theoretical basis for further improvement of the theoretical system for fire risk evaluation in shopping malls, and also exerts practical and guidance significance on timeous and effective early warning as well as prevention and control of building fires.

Research on Degree Evaluation of Rural Waste Recycling of Heilongjiang Province Based on the Integrated Evaluation Method

2011 ◽  
Vol 347-353 ◽  
pp. 1735-1739
Author(s):  
Jie Shang ◽  
Yuan Yao
Keyword(s):  
Index System ◽  
Agricultural Waste ◽  
Waste Recycling ◽  
Evaluation Index System ◽  
Evaluation Index ◽  
Heilongjiang Province ◽  
Entropy Weight ◽  
Development Direction ◽  
Entropy Weight Method ◽  
Weight Method

This paper has analyzed the degree of agricultural waste recycling utilization, and problems existing in current rural calculated degree of waste recycling in Heilongjiang province, using AHP and entropy weight method integrated and construct the rural waste recycling system, and points out that the evaluation index system of agricultural waste recycling after the development direction.,This paper has analyzed the degree of agricultural waste recycling utilization, and problems existing in current rural calculated degree of waste recycling in Heilongjiang province, using AHP and entropy weight method integrated and construct the rural waste recycling system, and points out that the evaluation index system of agricultural waste recycling after the development direction.

Application of Combination Evaluation for Academic Title Evaluation

2011 ◽  
Vol 50-51 ◽  
pp. 756-760
Author(s):  
Bao Feng Li ◽  
Jing Guo Qu ◽  
Pu Yu Hao
Keyword(s):  
Associate Professor ◽  
Topsis Method ◽  
Entropy Weight ◽  
Base Points ◽  
Subjective Weight ◽  
Evaluation Models ◽  
Entropy Weight Method ◽  
Weight Method ◽  
Double Base

In this paper, using the relevant data of 34 teaching staffs who participate in the academic title evaluation of associate professor in 2010, firstly it introduces the entropy weight method, Topsis method with subjective weight, Topsis method with objective weight and double base points method with subjective weight to evaluate and sort the performance of 34 teaching staffs. Secondly, two combination evaluation models are constructed to do the same work and the conclusions are more science and rational.

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