Results 21 to 30 of about 66,918,658 (250)

Research on Orderly Charge and Discharge Strategy of EV Based on QPSO Algorithm

IEEE Access, 2022
The change of electric vehicle (EV) cluster schedulable capacity in each period under multi-time scales has strong randomness and volatility. To ensure the trip demand and the charge and discharge cost of users, and increase the reliability of load ...
Haihong Bian, Zhengyang Guo, Chengang Zhou, Ximeng Wang, Shan Peng, Xiaoao Zhang   +5 more
doaj   +1 more source

Path Planning Method for AUV Docking Based on Adaptive Quantum-Behaved Particle Swarm Optimization

IEEE Access, 2019
AUV docking requires the platform to have both wide range cruising and accurate operating abilities, to against challenges of ocean currents, obstacles, and constraints.
Zeyu Li, Weidong Liu, Li-E Gao, Le Li, Feihu Zhang   +4 more
doaj   +1 more source

Compound particle swarm optimization in dynamic environments [PDF]

, 2008
Copyright @ Springer-Verlag Berlin Heidelberg 2008.Adaptation to dynamic optimization problems is currently receiving a growing interest as one of the most important applications of evolutionary algorithms.
Yang, S, Wang, Dingwei, Shengxiang Yang, Liu, Lili, Lili Liu, Dingwei Wang, Yang, Shengxiang, Wang, D, Liu, L   +8 more
core   +1 more source

Digital IIR filter design using particle swarm optimisation [PDF]

, 2010
Adaptive infinite-impulse-response (IIR) filtering provides a powerful approach for solving a variety of practical signal processing problems. Because the error surface of IIR filters is typically multimodal, global optimisation techniques are generally ...
Chen, Sheng, Luk, Bing L.
core   +1 more source

An Estimation of Distribution Particle Swarm Optimization Algorithm [PDF]

, 2006
In this paper we present an estimation of distribution par-ticle swarm optimization algorithm that borrows ideas from recent de-velopments in ant colony optimization.
Iqbal, Mudassar, Montes De Oca Roldan, Marco, Marco A. Montes de Oca, Mudassar Iqbal, de Oca, Marco A. Montes, Iqbal, Musaddar   +5 more
core   +1 more source

Particle Swarm Optimization Based on Local Attractors of Ordinary Differential Equation System

Discrete Dynamics in Nature and Society, 2014
Particle swarm optimization (PSO) is inspired by sociological behavior. In this paper, we interpret PSO as a finite difference scheme for solving a system of stochastic ordinary differential equations (SODE). In this framework, the position points of the
Wenyu Yang, Wei Wu, Yetian Fan, Zhengxue Li   +3 more
doaj   +1 more source

Optimized Particle Swarm Optimization (OPSO) and its application to artificial neural network training [PDF]

, 2006
Background: Particle Swarm Optimization (PSO) is an established method for parameter optimization. It represents a population-based adaptive optimization technique that is influenced by several "strategy parameters".
Meissner, Michael, Michael Schmuker (4736406), Schmuker Michael, Schneider, Gisbert (Prof. Dr.), Michael Meissner, Michael Schmuker, Gisbert Schneider, Schmuker, Michael, Gisbert Schneider (17096), Meissner Michael, Schneider Gisbert, Michael Meissner (17094)   +11 more
core   +1 more source

Hybridizing Chaotic and Quantum Mechanisms and Fruit Fly Optimization Algorithm with Least Squares Support Vector Regression Model in Electric Load Forecasting

Energies, 2018
Compared with a large power grid, a microgrid electric load (MEL) has the characteristics of strong nonlinearity, multiple factors, and large fluctuation, which lead to it being difficult to receive more accurate forecasting performances.
Ming-Wei Li, Jing Geng, Wei-Chiang Hong, Yang Zhang   +3 more
doaj   +1 more source

Feedback learning particle swarm optimization [PDF]

, 2011
This is the author’s version of a work that was accepted for publication in Applied Soft Computing. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may ...
Tang, Y, Zidong Wang, Wang, Z, Yang Tang, Fang, J, Jian-an Fang   +5 more
core   +1 more source

Modeling of Nonlinear Aggregation for Information Fusion Systems with Outliers Based on the Choquet Integral

Sensors, 2011
Modern information fusion systems essentially associate decision-making processes with multi-sensor systems. Precise decision-making processes depend upon aggregating useful information extracted from large numbers of messages or large datasets ...
Jin-Tsong Jeng, You-Min Jau, Kuo-Lan Su
doaj   +1 more source