Search Results - (( normal optimization method algorithm ) OR ( data distribution function algorithm ))
Search alternatives:
- normal optimization »
- function algorithm »
- data distribution »
- method algorithm »
-
1
A new variant of black hole algorithm based on multi population and levy flight for clustering problem
Published 2020“…The obtained results were compared with the BH and previous optimization algorithms for both test functions as well as data clustering in terms of normal and high dimensional datasets. …”
Get full text
Get full text
Thesis -
2
Automatic database of robust neural network forecasting / Saadi Ahmad Kamaruddin, Nor Azura Md. Ghani and Norazan Mohamed Ramli
Published 2014“…The direct idea of making the conventional neural network learning algorithm more powerful towards outlying data is by replacing the mean square error (MSE) with a different symmetric and continuous cost function. …”
Get full text
Get full text
Get full text
Book Section -
3
PSO modelling and PID controlled of automatic fish feeder system
Published 2020“…The main objective of this study is to improve the performance of fish feeding system by using PID controller through ARX modelling. In this study, raw data at distribution part with speed of 130 rpm, 160 rpm, 190 rpm, 220 rpm and 250 rpm were extracted and used to determine ARX equation parameters as transfer function by using PSO algorithm to optimize ARX model parameter. …”
Get full text
Get full text
Get full text
Get full text
Thesis -
4
Reservoir Inflow Forecasting Using Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System Techniques
Published 2007“…The reservoir inflow and rainfall data sets were examined for normal distribution and the best data transformation was used. …”
Get full text
Get full text
Thesis -
5
Enhancing clustering algorithm with initial centroids in tool wear region recognition
Published 2020“…Autonomous manufacturing allows the system to distinguish between a mild, normal and total failure in tool condition. K-means clustering has become the most applied algorithm in discovering classes in an unsupervised scenario. …”
Get full text
Get full text
Get full text
Get full text
Article -
6
Application of genetic algorithm methods to optimize flowshop sequencing problem
Published 2008“…Genetic algorithm method was one of the methods that were widely used in solving optimization problem. …”
Get full text
Get full text
Undergraduates Project Papers -
7
-
8
Normal-boundary intersection based parametric multi-objective optimization of green sand mould system
Published 2013“…In this work, a novel approach that merges meta-heuristic algorithms with the Normal Boundary Intersection (NBI) method is introduced. …”
Get full text
Get full text
Article -
9
Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques
Published 2018“…To deal with these problems, this thesis introduces three approved intelligent controllers for hydropower generation. Firstly, a hybrid algorithm namely firefly particle swarm optimization (FPSO) and series division method (SDM) based on the practical swarm optimization and the firefly algorithm is proposed. …”
Get full text
Get full text
Thesis -
10
-
11
Taguchi?s T-method with Normalization-Based Binary Bat Algorithm
Published 2025“…Therefore, a variable selection technique using a swarm-based Binary Bat algorithm is proposed. Specifically, a normalization-based Binary Bat algorithm is used, where discretization of continuous solution into binary form is performed using a normalization equation. …”
Conference paper -
12
-
13
An algorithmic framework for multiobjective optimization
Published 2013“…Various metaheuristic techniques such as differential evolution (DE), genetic algorithm (GA), gravitational search algorithm (GSA), and particle swarm optimization (PSO) have been used in conjunction with scalarization techniques such as weighted sum approach and the normal-boundary intersection (NBI) method to solve MO problems. …”
Get full text
Get full text
Article -
14
Scheduling scientific workflow in multi-cloud: a multi-objective minimum weight optimization decision-making approach
Published 2023“…A significant number of NP-hard problem optimization methods employ multi-objective algorithms. …”
Get full text
Get full text
Article -
15
-
16
Taguchi's method for optimized neural network based autoreclosure in extra high voltage lines
Published 2008“…The fault identification prior to reclosing is based on optimized artificial neural network associated with Levenberg Marquardt algorithm to train the ANN and Taguchi's Method to find optimal parameters of the algorithm and number of hidden neurons. …”
Get full text
Get full text
Get full text
Conference or Workshop Item -
17
Adaptive route optimization for mobile robot navigation using evolutionary algorithm
Published 2021“…For example, Ant Colony Optimization (ACO) is an optimization algorithm based on swarm intelligence which is widely used to solve path planning problem. …”
Get full text
Get full text
Get full text
Get full text
Proceedings -
18
Autoreclosure in Extra High Voltage Lines using Taguchi’s Method and Optimized Neural Networks
Published 2008“…The fault identification prior to reclosing is based on optimized artificial neural network associated with standard Error Back-Propagation, Levenberg Marquardt Algorithm and Resilient Back-Propagation training algorithms together with Taguchi’s Method. …”
Get full text
Get full text
Conference or Workshop Item -
19
Autoreclosure in Extra High Voltage Lines using Taguchi's Method and Optimized Neural Networks
Published 2009“…The fault identification prior to reclosing is based on optimized artificial neural network associated with standard Error Back-Propagation, Levenberg Marquardt Algorithm and Resilient Back-Propagation training algorithms together with Taguchi’s Method. …”
Get full text
Get full text
Conference or Workshop Item -
20
Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms
Published 2020“…The IEM algorithm uses the attraction-repulsion mechanism to change the positions of solutions towards the optimality. …”
Get full text
Get full text
Thesis