In this study, we used pso algorithm and ANN to predict annual electricity consumption in Iranian agriculture sector. The economic indicators used in this paper are price, value added, number of customers and consumpt...
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In this study, we used pso algorithm and ANN to predict annual electricity consumption in Iranian agriculture sector. The economic indicators used in this paper are price, value added, number of customers and consumption in the previous periods. To predict the future values, a linear-logarithmic model of electrical energy demand is considered. The pso algorithm applied in this study has been tuned for all its parameters and the best coefficients with minimum error are identified, while all parameter values are tested concurrently. Consumption in the previous periods has been used for testing estimated model. The estimation errors of pso algorithm are less than that of estimated by genetic algorithm and regression method. In addition, ANN is used to forecast each independent variable and then electricity consumption is forecasted up to year 2010. Electricity consumption in Iranian agriculture sector from 1981 to 2005 is considered as the case for this study.
The parameter of Dissolved Oxygen is one of great importance in the process of microbe fermentation. A normal PID is difficult to solve the nonlinear, time-delay characteristics. A intelligent PID controller is design...
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ISBN:
(纸本)9787811240559
The parameter of Dissolved Oxygen is one of great importance in the process of microbe fermentation. A normal PID is difficult to solve the nonlinear, time-delay characteristics. A intelligent PID controller is designed based on dynamic inertia factor pso, which can adaptively adjust the parameters of PID and is used in the control of DO. Compared with normal PID controller, the new controller is of small overshoot and quick response, improved stability of the system and increase the yield of products.
The magnitude of the original quality and original angle of hypersonic vehicle can influence flying orbit and other design-parameters greatly. Firstly, according to flying process, the flying orbit was divided into si...
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The magnitude of the original quality and original angle of hypersonic vehicle can influence flying orbit and other design-parameters greatly. Firstly, according to flying process, the flying orbit was divided into six states analyzed by three models. Then a modified particle swarm optimization (pso) algorithm was used to test the relationship among original quality, original angle and level distance. Referring to the test result, optimization research on a period of flying orbit of hypersonic vehicle was performed. Finally, the method has been successfully used and validated its rationality and validity by testing and analyzing the example.
Based on the study of Radial Basis Function(RBF) neural network training algorithm and Particle Swarm Optimization(pso) algorithm,a new RBF neural network training algorithm with modified pso algorithm is formulated,i...
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Based on the study of Radial Basis Function(RBF) neural network training algorithm and Particle Swarm Optimization(pso) algorithm,a new RBF neural network training algorithm with modified pso algorithm is formulated,in which a control gene is introduced into basis pso *** algorithm can determine network structure and parameters,such as centers and widths of hidden units by combining with least square *** new training algorithm is applied to the nonlinear system identification problem,comparing with hierachical genetic algorithm and orthogonal least squares algorithm(OLS),the simulation results illustrate its efficiency.
This paper provides a algorithm based on the microhabitat theory and particle swarm for the problem of Transformer Substation Optimiziation. This method can locate the substation according to muti-objects model of the...
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ISBN:
(纸本)9781424401109
This paper provides a algorithm based on the microhabitat theory and particle swarm for the problem of Transformer Substation Optimiziation. This method can locate the substation according to muti-objects model of the problem, give the best scheme in a certain load level, and reduce the difficulties and works. In the end of paper, a real project example is showed to prove the validity and feasibility.
Drilling path optimization is the key problem in holes machining. This paper presents a swarm intelligent approach based on the particle swarm optimization (pso) algorithm for solving the drilling path optimization pr...
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ISBN:
(纸本)9781424405701
Drilling path optimization is the key problem in holes machining. This paper presents a swarm intelligent approach based on the particle swarm optimization (pso) algorithm for solving the drilling path optimization problem. Because the standard pso algorithm is not guaranteed to be global convergence or local convergence, the algorithm is improved by adopting the method of generating the stop evolution particle over again to get the ability of convergence on the global optimization solution. And the operators are improved by establishing the order exchange unit and the order exchange list to satisfy the need of integer coding in drilling path optimization. The experimentations indicate that the improved algorithm has the characteristics of easy realization, fast convergence speed, and better global converging capability. Hence the new pso can play a role in solving the problem of drilling path optimization.
This paper investigates the economic order quantity (EOQ) inventory problem with imperfect quality items, where the percentages of defective items and poor-quality items in each delivered lot are assumed to be random ...
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ISBN:
(纸本)1424400600
This paper investigates the economic order quantity (EOQ) inventory problem with imperfect quality items, where the percentages of defective items and poor-quality items in each delivered lot are assumed to be random variables, and the inspection cost, holding cost, ordering cost are characterized as fuzzy variables, respectively. The fuzzy random expected value EOQ model and fuzzy random dependent chance programming (DCP) model are constructed. In addition, a particle swarm optimization (pso) algorithm based on fuzzy random simulation is designed to solve the presented DCP model. Finally, the effectiveness of the algorithm is illustrated by a numerical example.
This paper investigates the economic order quantity (EOQ) inventory problem with imperfect quality items, where the percentages of defective items and poor-quality items in each delivered lot are assumed to be random ...
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This paper investigates the economic order quantity (EOQ) inventory problem with imperfect quality items, where the percentages of defective items and poor-quality items in each delivered lot are assumed to be random variables, and the inspection cost, holding cost, ordering cost are characterized as fuzzy variables, respectively. The fuzzy random expected value EOQ model and fuzzy random dependent chance programming (DCP) model are *** addition, a particle swarm optimization (pso) algorithm based on fuzzy random simulation is designed to solve the presented DCP model. Finally, the effectiveness of the algorithm is illustrated by a numerical example.
A technique for Fuzzy Cognitive Maps learning,which is based on the Quantum-behaved Particle Swarm Optimization algorithm,is *** proposed approach is used for updating the nonzero weight values that lead the Fuzzy Cog...
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A technique for Fuzzy Cognitive Maps learning,which is based on the Quantum-behaved Particle Swarm Optimization algorithm,is *** proposed approach is used for updating the nonzero weight values that lead the Fuzzy Cognitive Map to desired steady *** workings of the approach are applied to an industrial control *** results support the claim that the proposed technique is a promising methodology for Fuzzy Cognitive Maps learning,and the methodology is effective and efficient.
Approaches to the determination of the minimum bounding box are widely used in mold, packing and layout design. One example in die and mold manufacture is the discrimination of whether a part can be made from standard...
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Approaches to the determination of the minimum bounding box are widely used in mold, packing and layout design. One example in die and mold manufacture is the discrimination of whether a part can be made from standard sized stock material. algorithms of determining the minimum bounding box are firstly introduced and analyzed in this paper. Novel methods of finding the minimum bounding box based on optimization algorithms are proposed. By applying optimization algorithms, the minimum bounding box of an arbitrary solid can be decided by rotating a block containing the solid. Simulation results show that proposed approaches are efficient and effective to the determination of the minimum bounding box of a solid.
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