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This work presents a study on prediction of university enrollment using three computational intelligence (CI) techniques. The enrollment forecasting has been considered as a form of time series prediction using CI techniques that include an artificial neural network (ANN), a neuro-fuzzy inference system (ANFIS) and an aggregated fuzzy time series model. A novel form of ANN, namely, single multiplicative...
It has become acceptable practice to use only a limit on the number of fitness function evaluations (FEs) as a stopping condition when comparing population-based optimization algorithms, irrespective of the initial number of candidate solutions. This practice has been advocated in a number of competitions to compare the performance of population-based algorithms, and has been used in many articles...
In view of the existing polygonal approximation algorithm of digital curves can't effectively solve the problem of polygonal approximation constrained by the offset direction, this paper proposes an algorithm of polygonal approximation constrained by the offset direction. First, the offset polygon of the original digital curve is calculated under the control of offset direction and distance. Second,...
Cuckoo search is a swarm-intelligence-based algorithm that is very effective for solving highly nonlinear optimization problems. In this paper, the multiobjective cuckoo search is extended so as to obtain high-quality Pareto fronts more accurately for multiobjective optimization problems with complex constraints. The proposed approach uses a combination of the cuckoo search with non-dominated sorting...
In this paper, a novel PSO based metaheuristic is proposed. This described approach is inspired by human gathering mechanisms. Each particle is given a possibility to follow a randomly selected particle from the swarm. When a promising search area is found by the particle, it remains stationary for a given number of iterations improving the chances of other particles following such a stationary particle...
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