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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...
As the breakage of old cement concrete in urban, the use of asphalt concrete overlay was more and more popular. Seldom actual test measurement datum and prediction and evaluation methods can be found. In order to scientifically and accurately predict the future composite pavement situation, evaluation indexes and main influence factors of composite pavement were analyzed. Then functional performance,...
A new approach based on BP neural network integrated with genetic algorithm for fitting of micro-drill's main lips is presented. The network structure is designed according to fitting equation, coordinates of micro-drill sampled points and constant 1 are taken as 3 inputs of network, 1 output is obtained, and the square of errors between the output and constant 0 is taken as performance index. Weights...
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...
A decision making architecture for intelligent agents is presented in this paper. It allows agents to perform autonomous behavior with respect to its own goals and cooperation with other agents. We focus on computational agents that encapsulate various methods of computational intelligence, such as neural networks, genetic algorithms, and similar methods. The goal of these agents is typically to solve...
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...
In school education there are many kinds of learning styles, and it is known that group learning (collaborative learning) is more effective than individual learning. In collaborative learning it is very important how to determine the optimal combination of students in order to improve the learning effect. In this paper we propose a method to improve the learning effect of collaborative learning. A...
This paper introduces a novel paradigm to impute missing data that combines a decision tree with an auto-associative neural network (AANN) based model and a principal component analysis-neural network (PCA-NN) based model. For each model, the decision tree is used to predict search bounds for a genetic algorithm that minimise an error function derived from the respective model. The modelspsila ability...
The coupled computational intelligence, in term of genetic algorithms and artificial neural networks, with the time-domain solver for design of the microwave devices is presented in this paper, where the coupled genetic algorithms with the time-domain solver is used for optimization and the artificial neural networks is used to surrogate the time-domain solver in design of the microwave components...
The following topics are dealt with: intelligent agents and ontologies; data mining, knowledge discovery and decision making; intelligent systems; Web technologies and Web services; virtual reality and games; image processing and image understanding techniques; adaptive control and automation; modelling, prediction and control; multi-agent systems and computational intelligence; agent systems, personal...
This paper discusses opportunities and challenges for the creation of evolving artificial neural network (ANN) and more general computational intelligence (CI) models inspired by principles at different levels of information processing in the brain - neuronal-, genetic-, and quantum - and mainly the issues related to the integration of these principles into more powerful and accurate ANN models. A...
This paper describes a computational intelligence-based software configuration implemented on semiconductor automatic test equipment (ATE) and how we can improve our design (e.g. memory test chip) based on such a method. The purpose of this unique software configuration incorporating neural network, genetic-algorithm and other artificial intelligence technologies is to enhance ATE capability and efficiency...
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