Search Results - optimal ((((force algorithm) OR (colony algorithm))) OR (cell algorithm))

Predicting breast cancer using ant colony optimisation / Siti Sarah Aqilah Che Ani by Che Ani, Siti Sarah Aqilah

“…Hence, the main purpose of this study is to develop a model of classification for breast cancer cell prediction. This study implements a machine learning algorithm called Ant Colony Optimization (ACO) algorithm to develop an accurate classification model for predicting breast cancer cells. …”
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Plant leaf recognition algorithm using ant colony-based feature extraction technique by Ghasab, Mohammad Ali Jan

“…Then, based on the characteristics of each species, decision making is done by means of ant colony optimisation as a search algorithm to return the optimal subset of features regarding the related species. …”
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Multi agent quality of service routing based on scheme ant colony optimization algorithm by Baygi, Maassoumeh Javadi

“…This research presents a per class QoS routing approach based on Ant Colony Optimization (ACO) called ACR-QoS to provide QoS for different Class of Services (CoSs). …”
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Enhanced gravitational search algorithm for nano-process parameter optimization problem / Norlina Mohd Sabri by Mohd Sabri, Norlina

“…In this research, the empirical experiments have been conducted for the five selected algorithms in the engineering optimization discipline, namely Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), Ant Colony Optimization (ACO) and Artificial Immune System (AIS). …”
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Improving energy efficiency of massive MIMO using small cell network: article by Mat Zim, Alizawati

“…For this paper, three beamforming (BF) algorithms are compared which are optimal BF is using only the base station (BS), multiflow regularized zero forcing (RZF) BF and optimal spatial soft-cell coordination BF. …”
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Improving energy efficiency of massive memo using small cell network / Alizawati Mat Zim by Mat Zim, Alizawati

“…For this paper, three beamforming (BF) algorithms are compared which are optimal BF is using only the base station (BS), multiflow regularized zero forcing (RZF) BF and optimal spatial soft-cell coordination BF. …”
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Application of system identification method coupled with evolutionary algorithms for the optimization of power consumption in a pem fuel cell propulsion system / Suhadiyana Hanapi by Hanapi, Suhadiyana

“…This thesis makes a number of key contributions to the advancement of fuel cell vehicle design within two main research areas; powertrain system design based on quality energy, and optimization system based on biology based algorithms. …”
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A Hybrid ANFIS-ABC Based MPPT Controller for PV System with Anti-Islanding Grid Protection: Experimental Realization by Padmanaban S., Priyadarshi N., Bhaskar M.S., Holm-Nielsen J.B., Ramachandaramurthy V.K., Hossain E.

“…Controllers; Distributed power generation; Electric inverters; Electric power system protection; Fuzzy control; Fuzzy inference; Fuzzy logic; Fuzzy neural networks; Fuzzy systems; Inference engines; Maximum power point trackers; Mean square error; Membership functions; Optimization; Photovoltaic cells; Adaptive neuro-fuzzy inference system; Anti-islanding protection; Artificial bee colony algorithms (ABC); Experimental realizations; Experimental validations; Fuzzy-logic control; Photovoltaic systems; Root mean square errors; Electric power system control…”

On spectral efficiency maximization in a partial joint processing system using a multi-start particle swarm optimization algorithm by Faisal, Ali Raed, Hashim, Fazirulhisyam, Ismail, Mahamod, Noordin, Nor Kamariah

“…Therefore stochastic multi-start particle swarm optimization algorithm (MSPSOA) is proposed in this paper to achieve backhaul reduction and address the issue of lack of diversity, which is related to the basic particle swarm optimization algorithm (BPSOA). …”
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Smart Semi-active PID-ACO control strategy for tower vibration reduction in Wind Turbines with MR damper by Rahman, Mahmudur, Ong, Zhi Chao, Chong, Wen Tong, Julai, Sabariah

“…PID control parameters are optimized using an Ant colony optimization (ACO) algorithm. …”
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A review on autonomous mobile robot path planning algorithms by Noraziah, Adzhar, Yuhani, Yusof, Muhammad Azrin, Ahmad

“…In this paper, commonly use classical approaches such as cell decomposition (CD), roadmap approach (RA), artificial potential field (AFP), and heuristics approaches such as genetic algorithm (GA), particle swarm optimization (PSO) approach and ant colony optimization (ACO) method are considered.It is observed that when it comes to dynamic environment where most of the information are unknown to the mobile robots before starting, heuristics approaches are more popular and widely used compared to classical approaches since it can handle uncertainty, interact with objects and making quick decision. …”
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Gait identification modelling for a hybrid amphi-underwater robot with exponential momentum ant colony algorithm by Toha, Siti Fauziah, Ahmad, Salmiah, Ismail, Amelia Ritahani, Abdul Hamid, Syamsul Bahrin

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Energy management system for optimal operation of microgrid consisting of PV, fuel cell and battery / Shivashankar Sukumar by Shivashankar , Sukumar

“…The BESS sizing problem is solved using grey wolf optimizer (GWO), particle swarm optimization (PSO), artificial bee colony (ABC), gravitational search algorithm (GSA), and genetic algorithm (GA). …”
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Backhaul load and performance optimality of partial joint processing schemes in LTE-A networks by Kousha, Mohammad

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Efficient beamforming and spectral efficiency maximization in a joint transmission system using an adaptive particle swarm optimization algorithm by Faisal, Ali Raed, Hashim, Fazirulhisyam, Noordin, Nor Kamariah, Ismail, Mahamod, Jamalipour, Abbas

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A review on path planning and obstacle avoidance algorithms for autonomous mobile robots by Anis Naema Atiyah, Rafai, Noraziah, Adzhar, Nor Izzati, Jaini

“…Taking into consideration commonly used classical approaches such as Dijkstra algorithm (DA), artificial potential field (APF), probabilistic road map (PRM), cell decomposition (CD), and meta-heuristic techniques such as fuzzy logic (FL), neutral network (NN), particle swarm optimization (PSO), genetic algorithm (GA), cuckoo search algorithm (CSO), and artificial bee colony (ABC). …”
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Minimization of tool path length of drilling process using particle swarm optimization (PSO) by Abdullah, Haslina, Zaman, Nizam Nurehsan, Talib, Norfazillah, Lee, Woon Kiow, Saleh, Aslinda, Zakaria, Mohamad Shukri

“…In various publications and articles, scientists and researchers adapted several methods of artificial intelligence (AI) or hybrid optimization method for tool path artificial immune system (AIS), genetic algorithms (GA), Artificial Neural networks (ANN) Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO) (Narooei and Ramli, 2014). …”
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A multi-layer perceptron for scheduling cellular manufacturing systems in the presence of unreliable machines and uncertain cost by Delgoshaei, Aidin, Gomes, Chandima

“…To solve the proposed problem, a number of metaheuristics are developed including Branch and Bound; Simulated Annealing algorithms; Fuzzy Art Control; Ant Colony Optimization and a hybrid Multi-layer Perceptron and Simulated Annealing algorithms. …”
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A new multiple ant colonies optimization algorithm utilizing average pheromone evaluation mechanism by Aljanaby, Alaa, Ku-Mahamud, Ku Ruhana, Md Norwawi, Norita

“…Multiple ant colonies optimization is an extension of the Ant Colony Optimization framework It offers a good opportunity to improve the ant colony optimization algorithms by encouraging the exploration of a wide area of the search space without losing the chance of exploiting the history of the search.This paper proposes a new multiple ant colonies optimization algorithm that is based on ant colony system and utilizes ave rage pheromone evaluation mechanism.The new algorithm divides the ants’ populations into multiple ant colonies and can be used to tackle large volume combinatorial optimization problems effectively. …”
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Interacted multiple ant colonies optimization approach to enhance the performance of ant colony optimization algorithms by Aljanaby, Alaa, Ku-Mahamud, Ku Ruhana, Md. Norwawi, Norita

“…One direction of ant colony optimization researches is dividing the ants’ population into several colonies. …”
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