scholarly journals Cable Tension Adjustment Based upon Fuzzy Theory and Genetic Algorithm.

2000 ◽  
pp. 143-151
Author(s):  
Masakatsu KANEYOSHI ◽  
Hitoshi FURUTA ◽  
Hiroshi TANAKA
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Theory ◽  
Cable Tension

Cable Tension Control of Cable-Stayed Bridge Using Fuzzy Satisfaction Method and Genetic Algorithm

2001 ◽  
Vol 84 (3) ◽  
pp. 39-46
Author(s):  
Hitoshi Furuta ◽  
Masakatsu Kaneyoshi ◽  
Hiroshi Tanaka ◽  
Eiichi Watanabe
Keyword(s):  
Genetic Algorithm ◽  
Tension Control ◽  
Cable Tension ◽  
Cable Stayed Bridge

Transformer Fault Diagnosis Based on Improved Quantum Genetic Algorithm and BP Network

2010 ◽  
Vol 29-32 ◽  
pp. 1543-1549 ◽  
Author(s):  
Jie Wei ◽  
Hong Yu ◽  
Jin Li
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Fault Diagnosis ◽  
Bp Neural Network ◽  
Fuzzy Theory ◽  
Back Propagation ◽  
Gas Analysis ◽  
Bp Network ◽  
Quantum Genetic Algorithm ◽  
Transformer Fault

Three-ratio of the IEC is a convenient and effective approach for transformer fault diagnosis in the dissolved gas analysis (DGA). Fuzzy theory is used to preprocess the three-ratio for its boundary that is too absolute. As the same time, an improved quantum genetic algorithm IQGA (QGASAC) is used to optimize the weight and threshold of the back propagation (BP). The local and global searching ability of the QGASAC approach is utilized to find the BP optimization solution. It can overcome the slower convergence velocity and hardly getting the optimization of the BP neural network. So, aiming at the shortcoming of BP neural network and three-ratio, blurring the boundary of the gas ratio and the QGASAC algorithm is introduced to optimize the BP network. Then the QGASAC-IECBP method is proposed in this paper. Experimental results indicate that the proposed algorithm in this paper that both convergence velocity and veracity are all improved to some extent. And in this paper, the proposed algorithm is robust and practical.

Decision Making in a Fuzzy Environment and its Management to the Diminishing Manufacturing Sources and Material Shortage Problems

2014 ◽  
Vol 513-517 ◽  
pp. 2672-2675
Author(s):  
Yuan Cheng Tsai ◽  
Yi Lun Chi
Keyword(s):  
Genetic Algorithm ◽  
Decision Making ◽  
Fuzzy Theory ◽  
Aerospace Industry ◽  
Possibility Theory ◽  
Lessons Learned ◽  
Fuzzy Environment ◽  
The Subject ◽  
Electronic Support

The paper formulated a proposed methodology to manage diminishing manufacturing sources and material shortage (DMS) with conclusions and recommendations on the subject of component obsolescence management in a military electronic support environment. By assessing applicable literature as well as feedback and lessons learned from relevant support projects, a strategy for the management of component obsolescence is proposed. The aim of the research is to explore the problem of managing DMS strategies by the method of project management and describes the risk of running distinct strategies to solve problems of DMS by fuzzy theory and possibility theory. Based on the results, this paper can be applied to support businesses quickly to determine the Strategies Combination, Resource Allocation and Inventory by using the model and genetic algorithm. A case study of an aerospace industry is used to illustrate the concept developed, which would be meaningful to reduce applicable obsolescence risks and thereby reducing related inventory and manpower costs.

scholarly journals Optimal Scheduling of Doctors Outpatient Departments Based on Patients’ Behavior

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Zongwei Ren ◽  
Haini Guo ◽  
Shizhen Bai ◽  
Peng Li
Keyword(s):  
Genetic Algorithm ◽  
Patient Satisfaction ◽  
Fuzzy Theory ◽  
Optimal Scheduling ◽  
Behavioral Characteristics ◽  
Large Hospital ◽  
Long Time ◽  
Service Oriented ◽  
Outpatient Departments ◽  
Better Than

The low operational efficiency in the field of medical and health care has become a serious problem in China; the long time that the patients have to wait for is the main phenomenon of difficult medical service. Medical industry is service-oriented and its main purpose is to make profits, so the benefits and competitiveness of a hospital depend on patient satisfaction. This paper makes a survey on a large hospital in Harbin of China and collects relevant data and then uses the prospect theory to analyze patients’ and doctors’ behavioral characteristics and the model of patient satisfaction is established based on fuzzy theory with a tripletα/β/γ. The optimal scheduling of clinic is described as a problem with the rule of first come, first served which maximizes patient satisfaction for the main goal and minimizes operating costs for the secondary goal. And the corresponding mathematical model is established. Finally, a solution method named plant growth simulation algorithm (PGSA) is presented. Then, by means of calculating of the example and comparing with genetic algorithm, the results show that the optimum can be reached; meanwhile the efficiency of the presented algorithm is better than the genetic algorithm.

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