Search Results - (( pattern search algorithm ) OR ((( patterns colony algorithm ) OR ( patterns path algorithm ))))*

Incremental continuous ant colony optimization for tuning support vector machine’s parameters by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…Hence, in applying Ant Colony Optimization for optimizing Support Vector Machine parameters, which are continuous in nature, the values wil have to be discretized.The discretization process will result in loss of some information and, hence, affects the classification accuracy and seeks time.This paper presents an algorithm to optimize Support Vector Machine parameters using Incremental continuous Ant Colony Optimization without the need to discretize continuous values.Eight datasets from UCI were used to evaluate the performance of the proposed algorithm.The proposed algorithm demonstrates the credibility in terms of classification accuracy when compared to grid search techniques, GA with feature chromosome-SVM, PSO-SVM, and GA-SVM.Experimental results of the proposed algorithm also show promising performance in terms of classification accuracy and size of features subset.…”
Get full text
Get full text
Get full text

Optimizing support vector machine parameters using continuous ant colony optimization by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…Hence, in applying Ant Colony Optimization for optimizing Support Vector Machine parameters, which are continuous parameters, there is a need to discretize the continuous value into a discrete value.This discretization process results in loss of some information and, hence, affects the classification accuracy and seek time.This study proposes an algorithm to optimize Support Vector Machine parameters using continuous Ant Colony Optimization without the need to discretize continuous values for Support Vector Machine parameters.Seven datasets from UCI were used to evaluate the performance of the proposed hybrid algorithm.The proposed algorithm demonstrates the credibility in terms of classification accuracy when compared to grid search techniques.Experimental results of the proposed algorithm also show promising performance in terms of computational speed.…”
Get full text
Get full text
Get full text

Traditional marble game using ant colony optimization / Muhammad Izzat Imran Che Isa by Che Isa, Muhammad Izzat Imran

“…The more number of marbles, the higher the search accuracy. In future, traditional marble game can be applied with other search algorithm to optimize the solution…”
Get full text
Get full text

Simulation performance comparison of A*, GLS, RRT and PRM path planning algorithms by Muhammad, Aisha, Nor Rul Hasma, Abdullah, Mohammad A.H., Ali, Shanono, Ibrahim Haruna, Rosdiyana, Samad

“…In this study, four robust path planning algorithms, namely: Probabilistic Roadmaps (PRMs), A-star, the Rapidly Exploring Random Trees (RRTs), and Generalized Laser Simulator (GLS), were simulated and their performance was measured and compared according to the total path distance covered, search time and path smoothness. …”
Get full text
Get full text
Get full text
Get full text

Ant colony algorithm for text classification in multicore-multithread environment / Ahmad Nazmi Fadzal by Fadzal, Ahmad Nazmi

“…Pheromone concept is the main criterion that distinguish ACO to other algorithms. Based on the concept, pheromone saturation is used to combine stackable solution pattern that is discovered while straying to different term node to build a path. …”
Get full text
Get full text

A generalized laser simulator algorithm for optimal path planning in constraints environment by Aisha, Muhammad

“…The suggested algorithm outperforms the competition in terms of improving path cost, smoothness, and search time. …”
Get full text

Hybrid ant colony system algorithm for static and dynamic job scheduling in grid computing by Alobaedy, Mustafa Muwafak Theab

“…This study proposed four hybrid algorithms between ACS, Genetic Algorithm (GA), and Tabu Search (TS) algorithms to enhance the ACS performance. …”
Get full text
Get full text
Get full text

Artificial neural networks based optimization techniques: A review by Abdolrasol M.G.M., Suhail Hussain S.M., Ustun T.S., Sarker M.R., Hannan M.A., Mohamed R., Ali J.A., Mekhilef S., Milad A.

“…In this paper, we present an extensive review of artificial neural networks (ANNs) based optimization algorithm techniques with some of the famous optimization techniques, e.g., genetic algorithm (GA), particle swarm optimization (PSO), artificial bee colony (ABC), and backtracking search algorithm (BSA) and some modern developed techniques, e.g., the lightning search algorithm (LSA) and whale optimization algorithm (WOA), and many more. …”

An improved ACS algorithm for data clustering by Mohammed Jabbar, Ayad, Ku-Mahamud, Ku Ruhana, Sagban, Rafid

“…However, ACOC suffers from high diversification in which the algorithm cannot search for best solutions in the local neighbourhood. …”
Get full text
Get full text
Get full text

Lexicon-based and immune system based learning methods in Twitter sentiment analysis by Jantan, Hamidah, Drahman, Fatimatul Zahrah, Alhadi, Nazirah, Mamat, Fatimah

“…In future work, the accuracy of proposed model can be strengthened by comparative study with other heuristic based searching algorithms such as genetic algorithm, ant colony optimization, swam algorithms and etc.…”
Get full text
Get full text
Get full text

Enhanced grey wolf optimisation algorithm for feature selection in anomaly detection by Almazini, Hussein

“…The third modification improves the controlled parameter of the MBGWO algorithm using indicators from the search process to refine the solution. …”
Get full text
Get full text

Optimization of economic lot scheduling problem with backordering and shelf-life considerations using calibrated metaheuristic algorithms by Mohammadi, M., Musa, S.N., Bahreininejad, A.

“…The aim is to determine the optimal production rate, production frequency, cycle time, as well as a feasible manufacturing schedule for the family of items, and to minimize the long-run average costs. Efficient search procedures are presented to obtain the optimum solutions by employing four well-known metaheuristic algorithms, namely genetic algorithm (GA), particle swarm optimization (PSO), simulated annealing (SA), and artificial bee colony (ABC). …”
Get full text
Get full text
Get full text

Development of behavior-based reactive navigation system for mobile robot by Mohd Hamami, Mohd Ghazali

“…The repeatability tests shown that the developed navigation algorithm able the robot to reach the target with the similar navigation path pattern outcome in each simulation tests. …”
Get full text
Get full text

Deterministic and stochastic inventory routing problems with backorders using artificial bee colony / Huda Zuhrah Ab Halim by Huda Zuhrah , Ab Halim

“…The inventory holding cost is assumed to be product specific and only incurred at the assembly plant. An Artificial Bee Colony (ABC) algorithm is proposed for the problem. …”
Get full text
Get full text
Get full text

New perturb and observe algorithm based on trapezoidal rule: uniform and partial shading conditions by Mahmod Mohammad Altwallbah, Neda, Mohd Radzi, Mohd Amran, Azis, Norhafiz, Shafie, Suhaidi, Mohd Zainuri, Muhammad Ammirrul Atiqi

“…For the first time, Trapezoidal rule concept is employed in P&O approach as a new consideration in the tracking process to calculate the best path for precisely tracking the GMPP. The new algorithm allows the search to continue until the extremum maximum is identified among numerous local maximums, rather than being imprisoned at one of the local maximums as is the case with the standard algorithm. …”
Get full text
Get full text

Artificial Bee Colony With Differential Evolution Algorithm For Feature Extraction And Selection Of Mass Spectrometry Data by Mohamed Yusoff, Syarifah Adilah

Get full text
Get full text

New Fast Block Matching Algorithm Using New Hybrid Search Pattern And Strategy To Improve Motion Estimation Process In Video Coding Technique by Hamid, Nurul 'Atiqah

“…There are 6 main designs that the algorithms proposed namely the Orthogonal-Diamond Search Algorithm with Small Diamond Search Pattern (ODS-SDSP), the Orthogonal-Diamond Search Algorithm with Large Diamond Search Pattern (ODS-LDSP), the Diamond-Orthogonal Search Algorithm with Small Diamond Pattern (DOS-SDSP), the Diamond-Orthogonal Search Algorithm with Large Diamond Pattern (DOS-LDSP), the Modified Diamond-Orthogonal Search Algorithm with Small Diamond Pattern (MDOS-SDSP), and the Modified Diamond-Orthogonal Search Algorithm with Large Diamond Pattern (MDOS-LDSP). …”
Get full text
Get full text
Get full text
Get full text

Neural Network Training Using Hybrid Particle-move Artificial Bee Colony Algorithm for Pattern Classification by Nuaimi, Zakaria Noor Aldeen Mahmood Al, Abdullah, Rosni

“…Artificial Bees Colony (ABC) optimization algorithm is one of the competitive algorithms in the SI algorithms group. …”
Get full text
Get full text
Get full text

Null positioning of dipole antenna array considering coupling effect by Abdul Malek, Norun, Mat Ramli, Nurwahida, Abdullah, Khaizuran

“…In forming the null, GA randomly searches the best fitness function to position the null to any direction. …”
Get full text
Get full text
Get full text

Neural network training using hybrid particle-move artificial bee colony algorithm for pattern classification by Al Nuaimi, Zakaria Noor Aldeen Mahmood, Abdullah, Rosni

“…In this work, we aimed to highlight the performance of the Hybrid Particle-move Artificial Bee Colony (HPABC) algorithm by applying it on the ANNT application.The performance of the HPABC algorithm was investigated on four benchmark pattern-classification data sets and the results were compared with other algorithms.The results obtained illustrate that HPABC algorithm can efficiently be used for ANNT.HPABC outperformed the original ABC and PSO as well as other state-of-art and hybrid algorithms in terms of time, function evaluation number and recognition accuracy.…”
Get full text
Get full text
Get full text