Search Results - (( java implementation bees algorithm ) OR ( parameter optimization connection algorithm ))
Search alternatives:
- optimization connection »
- parameter optimization »
- connection algorithm »
- java implementation »
- implementation bees »
- bees algorithm »
-
1
PID Parameters Improvement for AGC in Three Parallel-Connected Power Systems
Published 2016“…The AGC loop is used to minimize the frequency deviation and control the power exchange in order to maintain them at their scheduled values due to the changes of the step-load disturbance. The optimal parameters of the PID scheme optimized by the proposed MS algorithm are compared with that one’s obtained by GA algorithm, and the proposed method has proven that its performance is more efficient and improved as well. …”
Get full text
Get full text
Get full text
Conference or Workshop Item -
2
Profit-based optimal generation scheduling of a microgrid
Published 2023“…A case study on the difference between grid-connected and islanded operation is presented. The results demonstrate the efficiency of using genetic algorithm to solve the optimization problem. �2010 IEEE.…”
Conference paper -
3
A firefly algorithm based hybrid method for structural topology optimization
Published 2020“…In this paper, a firefly algorithm based hybrid algorithm through retaining global convergence of firefly algorithm and ability to generate connected topologies of optimality criteria (OC) method is proposed as an alternative method to solve stress-based topology optimization problems. …”
Get full text
Get full text
Article -
4
Dynamic user preference parameters selection and energy consumption optimization for smart homes using deep extreme learning machine and bat algorithm
Published 2020“…We applied a deep extreme learning machine approach to predict the user parameters. We have used the Bat algorithm and fuzzy logic to optimize energy consumption and comfort index management. …”
Get full text
Get full text
Get full text
Article -
5
Optimization of Off-Centre bracing system using Genetic Algorithm
Published 2011Get full text
Get full text
Article -
6
-
7
Grey wolf optimization for enhanced performance in wind power system with dual-star induction generators
Published 2025“…This comprehensive optimization ensures accurate parameter tuning for optimal system performance. …”
Article -
8
-
9
Forecasting of photovoltaic output using hybrid particle swarm optimization-artificial neural network model / Muhamad Faizol Adli Abdullah
Published 2010“…To overcome these problems, Particle Swarm Optimization (PSO) has been used to determine optimal value for BP parameters such as learning rate and momentum rate and also for weighting optimization. …”
Get full text
Get full text
Thesis -
10
-
11
Completion of contingency ranking selection (N-1) using ant colony optimization algorithm on 500 kV JAMALI system
Published 2022“…To ensure the power system's security, the Ant Colony Optimization (ACO) algorithm was used to run several contingency scenarios (N-1). …”
Get full text
Get full text
Get full text
Get full text
Proceeding Paper -
12
Fuzzy state space modeling for solving inverse problems in multivariable dynamic systems
Published 2005“…This algorithm is enhanced to address the optimization of parameters for a multiple-input multiple-output system, which leads to the derivation of an Extension of Optimized Defuzzified Value Theorem. …”
Get full text
Get full text
Thesis -
13
Genetic algorithm based method for optimal location placement of flexible ac transmission system devices for voltage profile improvement
Published 2011“…Most of the previous close studies have been performed to optimize two parameters i.e. location and rated value of each device only, while all the possible control parameters of each device including its location are optimized simultaneously in this study. …”
Get full text
Get full text
Thesis -
14
Optimal design of power system stabilizer for multimachine power system using farmland fertility algorithm
Published 2020“…The PSSs design problem is transformed into an optimization problem which an eigenvalue-based objective function is developed and both the GA, PSO and the proposed FFA optimization methods are applied to search for the optimal control parameters of the PSSs that are connected to the multimachine in the power system. …”
Get full text
Get full text
Get full text
Article -
15
Firefly algorithm-based neural network for GCPV system output prediction: article / Nor Syakila Mohd Zainol Abidin
Published 2014“…This paper presents a Multi-Layer Feedforward Neural Network (MLFNN) for predicting the AC power output from a grid-connected photovoltaic (GCPV) system. In the proposed MLFNN, Firefly Algorithm (FA) was employed as the optimizer and search tools of the MLFNN training parameters. …”
Get full text
Get full text
Article -
16
An intelligent voltage controller for a PV inverter system using simulated annealing algorithm-based PI tuning approach
Published 2023“…This study associates an intelligent voltage controller based PI approach for PV electrical inverter by employing a meta-heuristic optimization algorithmic called a Simulated Annealing (SA) algorithm. …”
Article -
17
Hybridization of metaheuristic algorithm in training radial basis function with dynamic decay adjustment for condition monitoring / Chong Hue Yee
Published 2023“…However, a drawback is that the performance of ANN is sensitive to the parameters (i.e., number of hidden neurons and the initial values of connection weights) in its architecture where the settings of these parameters are subject to tuning on a trial-and-error basis. …”
Get full text
Get full text
Get full text
Thesis -
18
-
19
Overview of Evolutionary Algorithms and Neural Networks for Modern Mobile Communication
Published 2024journal::journal article -
20
Mobility, Residual Energy, and Link Quality Aware Multipath Routing in MANETs with Q-learning Algorithm
Published 2019“…The MRLAM scheme uses a Q-Learning algorithm for the selection of optimal intermediate nodes based on the available status of energy level, mobility, and link quality parameters, and then provides positive and negative reward values accordingly. …”
Get full text
Get full text
Article
