IEEE World Congress on Computational Intelligence
نویسندگان
چکیده
منابع مشابه
Conference on Evolutionary Computation - IEEE World Congress on Computational
| In this paper we concentrate on non-preemptive hard real-time scheduling algorithms. We compare FIFO, EDLF, SRTF and genetic algorithms for solving this problem. The objective of the scheduling algorithm is to dynamically schedule as many tasks as possible such that each task meets its execution deadline, while minimizing the total delay time of all of the tasks. We present a MicroGA that use...
متن کاملA Modified Particle Swarm Optimizer - Evolutionary Computation Proceedings, 1998. IEEE World Congress on Computational Intelligence., Th
In this paper, we introduce a new parameter, called inertia weight, into the original particle swarm optimizer. Simulations have been done to illustrate the signilicant and effective impact of this new parameter on the particle swarm optimizer.
متن کاملConvergence in neural networks with interneuronal transmission delays - Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International
A neural network is a network of interconnected elementary units which have limited characteristic properties of real (or biological) neurons. Each unit is capable of receiving many inputs, some of which can activate the unit while other inputs can inhibit the activities of the unit. The neuron-like elementary unit computes a weighted sum of the input,s it receives and fires (or produces) a sin...
متن کاملImplementing radial basis functions using bump-resistor networks - Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International
Radial Basis Function (RBF) networks provide a powerful learning architecture for neural networks [6]. We have implemented a RBF network in analog VLSI using the concept of bump-resistors. A bump-resistor is a nonlinear resistor whose conductance is a Gaussian-like function of the difference of two other voltages. The width of the Gaussian basis functions may be continuously varied so that the ...
متن کاملMulti-Objective Genetic Local Search for Minimizing the Number of Fuzzy Rules for Pattern Classifica - Fuzzy Systems Proceedings, 1998. IEEE World Congress on Computational Intelligence., The 1998 IEEE
For constructing compact fuzzy rule-based systems with high classification performance, we have already formulated a rule selection problem. Our rule selection problem has two objectives: to minimize the number of selected fuzzy if-then rules (i.e., to minimize the fuzzy rule base) and to maximize the number of correctly classified patterns (i.e., to maximize the classification performance). In...
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ژورنال
عنوان ژورنال: IEEE Computational Intelligence Magazine
سال: 2023
ISSN: ['1556-6048', '1556-603X']
DOI: https://doi.org/10.1109/mci.2023.3282531