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Forestry Fire Spatial Diffusion Model Based On Integration Of Multi-Agent Algorithm With Cellular Automata, Zhao Di, Zhisheng Xu
Forestry Fire Spatial Diffusion Model Based On Integration Of Multi-Agent Algorithm With Cellular Automata, Zhao Di, Zhisheng Xu
Journal of System Simulation
Abstract: In view of the existing ultrasonic detection signal attenuation, directional difference, complex propagation paths, and characteristics of the components of complex, a kind of intelligent concrete defect nondestructive detection algorithm based on multi resolution singular entropy was put forward. By using the wavelet algorithm, the ultrasonic signal was decomposed into high, low frequency components of multi scales for each component, then each component was decomposed by singular spectrum analysis, at the same time using the information entropy theory, the calculation of singular entropy as the characteristic defect detection value, using the GA-SVM algorithm was used to train the singular …
Quality Control Method Based On Quantum Genetic Clustering Algorithm, Wang Jie, Wang Yan
Quality Control Method Based On Quantum Genetic Clustering Algorithm, Wang Jie, Wang Yan
Journal of System Simulation
Abstract: This paper proposes a method of quality control chart recognition based on Quantum Genetic Clustering Algorithm. This method is divided into two parts: quality feature extraction and pattern classification. By combining Quantum Genetic Algorithm(QGA) and K-means algorithm, a quantum genetic clustering algorithm based on a mechanism for determining the rotation direction of a quantum rotary gate is proposed, and its performance is verified by experimental simulation. Based on the clustering analysis of quality data using the quantum genetic algorithm proposed in this paper, a control chart feature description method is proposed. With this feature as input, Support Vector …
Heuristic Algorithm-Based Estimation Of Rotor Resistance Of An Induction Machine By Slot Parameters With Experimental Verification, Mehmet Çelebi̇, Murat Tören
Heuristic Algorithm-Based Estimation Of Rotor Resistance Of An Induction Machine By Slot Parameters With Experimental Verification, Mehmet Çelebi̇, Murat Tören
Turkish Journal of Electrical Engineering and Computer Sciences
The estimations of induction machine equivalent circuit parameters are still being widely used in the analysis and in determining the characteristics of the machine. Since the most important part of the machine is the rotor where torque is produced, the calculation of rotor resistance correctly will directly affect all other data. Almost all parameters belonging to the stator side can easily be determined through external measurements. However, due to the formulation of the rotor as a closed box, estimating rotor resistance and the rotor's slot shape by heuristic algorithms, without damaging the rotor physically, and comparing it with its actual …
Fractional Pid Controllers Tuned By Evolutionary Algorithms For Robot Trajectory Control, Zafer Bi̇ngül, Oğuzhan Karahan
Fractional Pid Controllers Tuned By Evolutionary Algorithms For Robot Trajectory Control, Zafer Bi̇ngül, Oğuzhan Karahan
Turkish Journal of Electrical Engineering and Computer Sciences
The aim of this paper is to compare the performances of a fractional order proportional integral derivative (FOPID) controller tuned with evolutionary algorithms for robot trajectory control. In order to make this comparison, a 2-degrees-of-freedom planar robot was controlled by a FOPID controller tuned with particle swarm optimization (PSO) and a real coded genetic algorithm (GA). In order to see the effects of the cost functions on the optimum parameters of the FOPID controller, 3 different cost functions were used: the root mean squared error (MRSE), mean absolute error (MAE), and mean minimum fuel and absolute error (MMFAE). In order …
Genetically Engineered Adaptive Resonance Theory (Art) Neural Network Architectures, Ahmad Al-Daraiseh
Genetically Engineered Adaptive Resonance Theory (Art) Neural Network Architectures, Ahmad Al-Daraiseh
Electronic Theses and Dissertations
Fuzzy ARTMAP (FAM) is currently considered to be one of the premier neural network architectures in solving classification problems. One of the limitations of Fuzzy ARTMAP that has been extensively reported in the literature is the category proliferation problem. That is Fuzzy ARTMAP has the tendency of increasing its network size, as it is confronted with more and more data, especially if the data is of noisy and/or overlapping nature. To remedy this problem a number of researchers have designed modifications to the training phase of Fuzzy ARTMAP that had the beneficial effect of reducing this phenomenon. In this thesis …