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Optimal Power Flow (OPF) is one of the most vital tools for power system operation analysis, which requires a complex mathematical formulation to find the best solution. Conventional methods such as Linear Programming, Newton-Raphson and Non-linear Programming were previously offered to tackle the complexity of the OPF. However, with the emergence of artificial intelligence, many novel techniques...
This paper combines artificial neural networks (ANN), fuzzy optimization and time-series econometric models in one unified framework to form a hybrid intelligent early warning system (EWS) for predicting economic crises. Using quarterly data on 12 macroeconomic and financial variables for the Chinese economy during 1999 and 2008, the paper finds that the hybrid model possesses strong predictive power...
Artificial Neural Network (ANN) is one of the most promising biological inspired computational intelligence techniques. However designing an ANN is a difficult task as it requires setting of ANN structure and tuning of some complex parameter. On the other hand, Genetic Algorithm (GA) as a global search technique is useful for complex optimization problem where the numbers of parameters are large and...
This paper presents the development of an Artificial Neural Networks and Particle Swarm Optimization (ANN-PSO) based short-term load forecasting model with improved generalization technique for the Regional Power Control Center of Saudi Electricity Company, Western Operation Area (SEC-WOA). Weather, load demand, wind speed, wind direction, heat, sunlight, etc. are quite different in a desert land...
This paper presents artificial neural networks and particle swarm optimization (ANN-PSO) based short-term load forecasting model with improved generalization technique for the regional power control center of Saudi Electricity Company, Western Operation Area (SEC-WOA) of Saudi Arabia. Weather, load demand, wind speed, wind direction, heat, sunlight, etc. are quite different in a desert land than other...
A novel methodology deals with the peaks overlapping issue in quantifying metabolites in MRSI is proposed in this paper. The introduced method encounters the metabolites quantification procedure as a typical optimization problem able to be solved by using optimization methods of the computational intelligence. A simple genetic algorithm is applied in order to find the metabolites peaks parameters...
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