Evolving artificial neural network and imperialist competitive algorithm for prediction oil flow rate of the reservoir

MA Ahmadi, M Ebadi, A Shokrollahi, SMJ Majidi - Applied Soft Computing, 2013 - Elsevier
Multiphase flow meters (MPFMs) are utilized to provide quick and accurate well test data in
numerous numbers of oil production applications like those in remote or unmanned …

A cost-effective multi-verse optimization algorithm for efficient power generation in a microgrid

U Lakhina, I Elamvazuthi, N Badruddin, A Jangra… - Sustainability, 2023 - mdpi.com
Renewable energy sources (RESs) are a great source of power generation for microgrids
with expeditious urbanization and increase in demand in the energy sector. One of the …

An Enhanced Multi-Objective Optimizer for Stochastic Generation Optimization in Islanded Renewable Energy Microgrids

U Lakhina, N Badruddin, I Elamvazuthi, A Jangra… - Mathematics, 2023 - mdpi.com
A microgrid is an autonomous electrical system that consists of renewable energy and
efficiently achieves power balance in a network. The complexity in the distribution network …

Multiobjective optimization of green sand mould system using chaotic differential evolution

T Ganesan, I Elamvazuthi, KZK Shaari… - … on Computational Science …, 2013 - Springer
Many industrial optimization cases present themselves in a multi-objective (MO) setting
(where each of the objectives portrays different aspects of the problem). Therefore, it is …

Swarm intelligence for multiobjective optimization of extraction process

T Ganesan, I Elamvazuthi, P Vasant - Handbook of Research on …, 2016 - igi-global.com
Multi objective (MO) optimization is an emerging field which is increasingly being
implemented in many industries globally. In this work, the MO optimization of the extraction …

Hypervolume-driven analytical programming for solar-powered irrigation system optimization

T Ganesan, I Elamvazuthi, KZK Shaari… - … : Prediction, Modeling and …, 2013 - Springer
In the field of alternative energy and sustainability, optimization type problems are regularly
encountered. In this paper, the Hypervolume-driven Analytical Programming (Hyp-AP) …

An intelligent control of Blood Pressure system using PID and Neural Network

I Elamvazuthi, OM Aymen, Y Salih… - 2013 IEEE 8th …, 2013 - ieeexplore.ieee.org
This paper presents an intelligent control approach for Blood Pressure (BP) system using
PID-Neural Network (PIDNN). This paper discusses the use of PIDNN to optimize the …

Multiobjective optimization using particle swarm optimization with non-Gaussian random generators

T Ganesan, P Vasant… - Intelligent Decision …, 2016 - content.iospress.com
In engineering optimization, multi-objective (MO) problems are frequently encountered. In
this work, a real-world MO problem (resin-bonded sand mould system) is tackled using …

Game-theoretic differential evolution for multiobjective optimization of green sand mould system

T Ganesan, P Vasant, I Elamvazuthi, KZK Shaari - Soft Computing, 2016 - Springer
Many large-scale engineering problems often take a multiobjective form. Thus, several
solution options to the MO problem are usually ascertained by the engineer. Then the most …

Evaluation of genetic algorithm as learning system in rigid space interpretation

BK Singh - Handbook of research on novel soft computing …, 2014 - igi-global.com
Genetic Algorithm (GA)(a structured framework of metaheauristics) has been used in various
tasks such as search optimization and machine learning. Theoretically, there should be …