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Krill herd algorithm is a new heuristic global optimization algorithm based on swarm intelligence. As the parameters are critical to the algorithm performance, they should be reasonably selected while applying krill herd algorithm to solve global optimization problems. In this paper, three parameters are included in the test analysis based on the comparison of six benchmark functions. The results...
This paper presents a new concept of building classification-type loss for regression sample based on conversion between regression and classification problems used in Support Vector Regression (SVR). By introducing the classification-type loss to calculate example's error, AdaBoost algorithm can be generalized from classification to regression. A new Boosting algorithm for regression, called AdaBoost...
The paper gives an improved particle swarm optimal algorithm in which a kind of exponent decreasing inertia weights is given to improve the convergence speed and a kind of stochastic mutations is used to improve the diversity of the swarm in order to overcome the disadvantage of premature convergence and later period oscillatory occurrences. It is shown by five representative benchmarks functionpsilas...
Accuracy parameters of system model are of great importance in stability and security evaluation or simulation for power system. Some of the conventional methods may have inadequate adaptability or effectiveness for identification of different power systems. A new framework for power system identification is proposed based on an improved genetic algorithm with a logarithmic fitness function and an...
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