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In this research, we propose to use a Genetic Algorithm with an Artificial Neural Network as fitness function in order to solve one of the most important problems in predicting academic success in higher education environments. Which is to find what are the factors that affect the students' academic performance. Also, using the same Artificial Neural Network as a predictor. To solve the problem, each...
The paper deals with a soft computing state control method for multi input — multi output (MIMO) non-linear dynamic model of a robot. Soft methods based on neural networks and genetic algorithms have proven their effectiveness for this application. They are based on quite simple principles, but take advantage of their mathematical nature: non-linear iterative computation solutions. One way of controlling...
The following topics are dealt with: intelligent system design; neural networks, AI and expert systems; evolutionary computation; genetic algorithms; natural language processing & machine translation; artificial life and artificial immune systems; rough and fuzzy rough set; gray system and cloud computing; cognitive radio and computer vision; pattern recognition and machine learning; fuzzy system...
Fuzzy logic is a topic traditionally taught in artificial intelligence, machine learning, and robotics courses. Students receive the necessary mathematical and theoretical foundation in lecture format. The final learning experience may require that students create and code their own fuzzy logic application that solves a real world problem. This can be an issue when the target is a bioengineering course...
This paper describes the use of soft computing based techniques toward the acquisition of adaptive behaviors to be used in mobile exploration by cooperating robots. Navigation within unknown environments and the obtaining of dynamic behavior require some method of unsupervised learning given the impossibility of programming strategies to follow for each individual case and for every possible situation...
This article focuses on the use of multi-agent systems for modelling of micro-unmanned aerial vehicles (MAVs) in a distributed control task. The task regards a search and destroy scenario in the context of security and urban counter-terrorism. In the simulations developed, a swarm composed of four autonomous flying robots, driven by an embodied neural network controller, has to approach a target deployed...
The following topics are dealt with: cybernetics and intelligent systems; adaptive computing; agents; computational intelligence; computer vision; pattern recognition; data mining and management; automation and robotics in biomolecular computing; intelligent data processing; image processing; particle swarm optimization; evolutionary computation; fuzzy control; genetic algorithms; neural networks;...
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