Comprehensive evaluation of integrative drip-irrigation and fertilization using a projection pursuit model based on the improved double chains quantum genetic algorithm

2017 ◽  
Vol 66 ◽  
pp. 229-234 ◽  
Author(s):  
Bai Wang ◽  
Yanfeng Li, ◽  
Yan Meng ◽  
Xiao Liu
Keyword(s):  
Genetic Algorithm ◽  
Drip Irrigation ◽  
Comprehensive Evaluation ◽  
Projection Pursuit ◽  
Quantum Genetic Algorithm ◽  
Model Based ◽  
Projection Pursuit Model

scholarly journals Competitiveness Evaluation of Chinese Dairy Industry Based on Accelerated Genetic Algorithm Projection Pursuit Model

2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Chen Hongli ◽  
Wu Yanyan ◽  
Liu Xiuli ◽  
Zhang Wenju
Keyword(s):  
Genetic Algorithm ◽  
Comprehensive Evaluation ◽  
Evaluation Model ◽  
Dairy Industry ◽  
Projection Pursuit ◽  
Development Trend ◽  
Northern Region ◽  
Positive Trend ◽  
Five Dimensions ◽  
Projection Pursuit Model

Scientific evaluation of the competitiveness of China’s dairy industry is of great significance to the development of regional dairy industry. In view of the fact that the existing evaluation model cannot solve the dynamic nonlinear optimization problem, this paper established a projection pursuit model based on accelerating genetic algorithm and carried on the comprehensive evaluation and dynamic analysis on the competitiveness of dairy industry in China’s 31 provinces and cities (not including Hong Kong, Macao, and Taiwan) from five dimensions, namely, basic factors of production, the industry demand conditions, the enterprise competitiveness and growth force, related and supporting industries, and the natural environmental elements. It was found that firstly, from the perspective of time, the development trend of China’s dairy industry basically shows a positive trend. With the improvement of national living standards, the competitiveness of the dairy industry is also constantly improved. Secondly, from the perspective of space, regional differences in the competitiveness of the dairy industry are significant. Inner Mongolia, Heilongjiang, Shandong, and Hebei are at the forefront of the development of the industry, while the development of the dairy industry in the rest of the region has a big gap with those areas. From the perspective of regional layout, the advantageous region of China’s dairy industry has been preliminarily formed, and the competitive advantage is mainly concentrated in the northern region. Accordingly, the countermeasures and suggestions to enhance the competitiveness of China’s dairy industry were put forward.

Comprehensive Evaluation of Sludge Treatment Schemes Based on Projection Pursuit Model

2014 ◽  
Vol 889-890 ◽  
pp. 1604-1608
Author(s):  
Gong Gao
Keyword(s):  
Comprehensive Evaluation ◽  
Projection Pursuit ◽  
Urban Rivers ◽  
Sludge Treatment ◽  
Evaluation Indexes ◽  
The Public ◽  
New Ideas ◽  
Projection Pursuit Model ◽  
Government Benefits ◽  
Selection Of

To explore new ideas for treating sludge in the urban rivers, 4 different sludge treatment schemes were proposed, the construction safety, projection duration, enthusiasm of the public, environmental coordination, resource utilization, supporting of government, benefits, and project cost of the schemes were selected as the main evaluation indexes, and the projection pursuit model was introduced to evaluate the schemes comprehensively. Results showed that: the evaluation and selection of sludge treatment schemes conformed to the calculation requirements of the projection pursuit model; S3 was the optimal sludge treatment scheme with best comprehensive benefits, the projection value of which was recorded as 1.198, much more than that of other treatments. Therefore, it was concluded that using sludge to produce brick (S3) was more appropriate for the sludge treatment in urban rivers, and which depended on the wide market of bricks and had good practical benefits. The study achievements could provide beneficial basis for the river management and the sludge treatment in cities, and also provide the practical basis for the application of statistical models on the selection of project schemes.

The Coal Slurry Pipeline Pressure Prediction Research Based on Quantum Genetic BP Neural Network

2013 ◽  
Vol 336-338 ◽  
pp. 722-727
Author(s):  
Xue Cun Yang ◽  
Yuan Bin Hou ◽  
Ling Hong Kong
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Prediction Model ◽  
Bp Neural Network ◽  
Thermal Power ◽  
Coal Slurry ◽  
Cylinder Pressure ◽  
Master Cylinder ◽  
Quantum Genetic Algorithm ◽  
Model Based

According to the coal slime pipeline blockage problem of coal gangue thermal power plant, after the analysis of the actual scene, it is sure that thick slurry pump master cylinder pressure prediction is the necessary premise of blockage prediction. The thick slurry pump master cylinder pressure prediction model is proposed, which is based on QGA-BP (Quantum genetic Algorithm BP neural network). The simulation results show that the prediction model based on QGA-BP can be used to predict the paste pump outlet pressure, and the relative error is less than 8%, which can satisfy the engineering requirement .And compared with prediction model based on GA-BP(the genetic Algorithm BP neural network), The QGA-BP prediction model is better than GA-BP model in prediction accuracy and optimization time.

Comprehensive Evaluation of Drill Wear Based on the Model of Projection Pursuit

2014 ◽  
Vol 602-605 ◽  
pp. 272-276
Author(s):  
Li Li Zhao ◽  
Yu Cai Dong ◽  
Lu Liu ◽  
Guan Yu Kou ◽  
Min Lin ◽  
...  
Keyword(s):  
Optimization Problems ◽  
Comprehensive Evaluation ◽  
Projection Pursuit ◽  
Weight Coefficient ◽  
Good Effect ◽  
Projection Data ◽  
Projection Direction ◽  
Optimal Projection ◽  
Projection Pursuit Model ◽  
Wear Evaluation

To overcome the deviation caused by the effect of subjective factors in drill wear evaluation, and make the evaluation more accurate and objective, on the basis of drill wear comprehensive evaluation criterion, the projection data are built with projection pursuit method. Two hundred drill wear comprehensive evaluation samples are randomly generated within the range of each class. The projection pursuit model is built by unitary processing according to these samples, which converts the evaluation into non-linear multi-constrained optimization problems. The optimal projection direction vector and the weight coefficient of each evaluation index are obtained with composite simplex method. Meanwhile the corresponding relationship between the region of variation of projection eigenvalue and classification grade is established. The precision of sample evaluation reaches 100% and the evaluation of the measured data achieves good effect. Thus, the scientific evaluation of drill wear is realized by the projection pursuit model.

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