Search Results - (( using action method algorithm ) OR ( basic optimization bees algorithm ))

A hybrid algorithm based on artificial bee colony and artificial rabbits optimization for solving economic dispatch problem by Lee, Wei Wen, Hashim, Mohd Ruzaini

“…Hence, a hybrid optimization algorithm called Artificial Bee Rabbit Optimization (ABRO) is proposed in this paper. …”
Get full text
Get full text
Get full text

Artificial bee colony algorithm with proposed discrete nearest neighborhood algorithm for discrete optimization problems by Rahimi, Amir Masoud, Ramezani-Khansari, Ehsan

“…To reduce the optimization time of the tours created by the artificial bee colony algorithm, the fixed-radius near neighbor 2-opt algorithm was used as well. …”
Get full text
Get full text
Get full text

Local search manoeuvres recruitment in the bees algorithm by Muhamad, Zaidi, Mahmuddin, Massudi, Nasrudin, Mohammad Faidzul, Sahran, Shahnorbanun

“…The Bees Algorithm (BA) was created specifically by mimicking the foraging behavior of foraging bees in searching for food sources.During the searching, the original BA ignores the possibilities of the recruits being lost during the flying.The BA algorithm can become closer to the nature foraging behavior of bees by taking account of this phenomenon.This paper proposes an enhanced BA which adds a neighbourhood search parameter which we called as the Local Search Manoeuvres (LSM) recruitment factor.The parameter controls the possibilities of a bee extends its neighbourhood searching area in certain direction.The aim of LSM recruitment is to decrease the number of searching iteration in solving optimization problems that have high dimensions.The experiment results on several benchmark functions show that the BA with LSM performs better compared to the one with basic recruitment.…”
Get full text
Get full text
Get full text

The design and applications of the african buffalo algorithm for general optimization problems by Odili, Julius Beneoluchi

“…Some of the successfully designed stochastic algorithms include Simulated Annealing, Genetic Algorithm, Ant Colony Optimization, Particle Swarm Optimization, Bee Colony Optimization, Artificial Bee Colony Optimization, Firefly Optimization etc. …”
Get full text
Get full text

Data Analysis using Particle Swarm Optimization Algorithm by Tai, Zu Jie

Get full text
Get full text

Adaptive mechanism for enhanced performance of shark smell optimization / Nur Atharah Kamarzaman, Shahril Irwan Sulaiman and Intan Rahayu Ibrahim by Kamarzaman, Nur Atharah, Sulaiman, Shahril Irwan, Ibrahim, Intan Rahayu

“…Numerical results indicate that the ASSO algorithm strategy outperforms the basic SSO algorithm, Genertic Algorithm (GA), Particle Swarm Intelligence (PSO), Firefly Algorithm (FA), Artificial Bee Colony (ABC) and Teaching Learning Based Optimization (TBLO) in term of reaching for global solution.…”
Get full text
Get full text
Get full text

Basic concept of implementing Artificial Bee Colony (ABC) system in flow shop scheduling by Ho, Yoong Chow, Hasan, Sulaiman, Bareduan, Ahmad Salleh

Get full text
Get full text
Get full text

Hybrid artificial bee colony algorithm with branch and bound for two–sided assembly line balancing by Elteriki, Salem Abdulsalam

“…Recently, the artificial bee colony (ABC) algorithm was used in the solution process where it was considered as a very useful, effective and well-known algorithm. …”
Get full text
Get full text
Get full text
Get full text

An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP by Bibi Aamirah Shafaa Emambocus, Muhammed Basheer Jasser, Muzaffar Hamzah, Aida Mustapha, Angela Amphawan

“…Since there is no known polynomial-time algorithm for solving large scale TSP, metaheuristic algorithms such as Ant Colony Optimization (ACO), Bee Colony Optimization (BCO), and Particle Swarm Optimization (PSO) have been widely used to solve TSP problems through their high quality solutions. …”
Get full text
Get full text
Get full text
Get full text
Get full text

Novel Multi-swarm Approach for Balancing Exploration and Exploitation in Particle Swarm Optimization by Salih, Sinan Q., Alsewari, Abdulrahman A., Al-Khateeb, Bellal, Mohamad Fadli, Zolkipli

Get full text
Get full text
Get full text

Optimization of supply chain management by simulation based RFID with XBEE Network by Soomro, Aftab Ahmed

“…In order to solve this problem, a simulation based “Multi-Colony Global Particle Swarm Optimization (MC-GPSO)” algorithm was developed. This algorithm computes the optimal results of objective functions in a scientific manner. …”
Get full text
Get full text
Get full text

STUDIES ON COMPARISON OF PROPORTIONAL ON ERROR WITH PROPORTIONAL ON MEASURED VALUE IN PID CONTROLLERS by WAN MOHD RUSHIDI, WAN AMIR HAKIMI

“… PID Controllers have different algorithms or methods in which the controller action is based on Error or Process Variable (PV). …”
Get full text
Get full text

An Improved Action Key Frames Extraction Algorithm for Complex Colour Video Shot Summarization by Mizher, Manar Abduljabbar Ahmad, Ang, Mei Choo, Sheikh Abdullah, Siti Norul Huda, Kok, Weng Ng

“…We then evaluated the Improved AKF algorithm with the-state-of-the-art algorithms in terms of compression ratio using Paul videos and Shih-Tang dataset. …”
Get full text
Get full text

Revolutionizing video analytics: a review of action recognition using 3D by Jeddah, Yunusa Mohammed, Hassan Abdalla Hashim, Aisha, Khalifa, Othman Omran, Ibrahim, Adamu Abubakar

“…As an interdisciplinary field, the 3D video action recognition model interprets human actions in three-dimensional video data using approaches such as pose-based, volumetric, motionbased, and hybrid methods. 3D video action recognition finds application in surveillance, sports analysis, human-computer interaction, healthcare, robotics, and augmented/virtual reality. …”
Get full text
Get full text

Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof by Yusof, Yusman

“…From the reviews, it is evident that autonomous system is set to handle finite number of encountered states using finite sequences of actions. In order to learn the optimized states-action policy the self-learning algorithm is developed using hybrid AI algorithm by combining unsupervised weightless neural network, which employs AUTOWiSARD and reinforcement learning algorithm, which employs Q-learning. …”
Get full text
Get full text

Simulation of an adaptive artificial neural network for power system security enhancement including control action by Al-Masri, Ahmed Naufal A., Ab Kadir, Mohd Zainal Abidin, Hizam, Hashim, Mariun, Norman

“…This paper presents a new method for enhancing power system security, including a remedial action, using an artificial neural network (ANN) technique. …”
Get full text
Get full text
Get full text

A new ant based rule extraction algorithm for web classification by Ku-Mahamud, Ku Ruhana, Saian, Rizauddin

Get full text
Get full text
Get full text
Get full text

Particle swarm optimization with deep learning for human action recognition by Usmani, U.A., Watada, J., Jaafar, J., Aziz, I.A., Roy, A.

“…This paper proposes a deep learning framework for human action recognition to overcome the drawbacks of the current state-of-the-art methods. …”
Get full text
Get full text

Adaptive artificial neural network for power system security assessment and control action by Al-Masri, Ahmed Naufal A.

“…This is particularly important for giving a possible control action to mitigate an insecure situation during disturbance using AANN. …”
Get full text
Get full text

Newton competitive genetic algorithm method for optimization the production of biochemical systems by Ismail, Mohd Arfian, Ab Razak, Kirahman, Kohbalan, Moorthy, Mezhuyev, Vitaliy, Kasim, Shahreen, Ibrahim, Ashraf Osman

“…In this work, the optimization of biochemical systems production is performed by using a hybrid method of Newton competitive genetic algorithm is presented. …”
Get full text
Get full text