Search Results - ((canopy algorithm) OR (ant algorithm))

An adaptive ant colony optimization algorithm for rule-based classification by Al-Behadili, Hayder Naser Khraibet

“…Ant-Miner is a variant of ant colony optimisation and a prominent intelligent algorithm widely use in rules-based classification. …”
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Ant colony optimization in dynamic environments by Chen, Fei Huang

“…In order to achieve this objective, six ant algorithms namely Ant System (AS), Ant Colony System (ACS), Best-Worst Ant System (BWAS), Elitist Ant System (EAS), Max-Min Ant System (MMAS) and Rank-Based Ant System (RBAS) were implemented to solve a dynamic optimization problem in the form of the dynamic Traveling Salesman Problem (TSP). …”
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Interacted Multiple Ant Colonies for Search Stagnation Problem by Aljanabi, Alaa Ismael

“…The experimental results show the superiority of the proposed approach than existing one colony ant algorithms like the ant colony system and max-min ant system. …”
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Enhancement of Ant System Algorithm for Course Timetabling Problem by Djamarus, Djasli

“…This research starts with developing an algorithm based on original concept of Ant System Algorithm. …”
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Predicting attackers of online shaming using ant colony optimization / Noor Shafiqa Fazlien Mohamad Fauzi by Mohamad Fauzi, Noor Shafiqa Fazlien

“…The Ant Miner system plays an important role in running the Ant Colony Optimization Algorithm and making comparison in this case study.…”
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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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Adaptive parameter control strategy for ant-miner classification algorithm by Al-Behadili, Hayder Naser Khraibet, Sagban, Rafid, Ku-Mahamud, Ku Ruhana

“…This paper presents a new hybrid Ant-Miner classification algorithm and ant colony system (ACS), called ACS-Ant Miner. …”
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An Enhanced Ant Colony Optimisation Algorithm with the Hellinger Distance for Shariah-Compliant Securities Companies Bankruptcy Prediction by Zainol, Annuur Zakiah, Saian, Rizauddin, Teoh, Yeong Kin, Mohd Razali, Muhammad Hasbullah, Abu Bakar, Sumarni

“…Hence, this study proposes an improved algorithm, the Hellinger Distance Ant-Miner (HD-AntMiner), which employs Hellinger distance as the heuristic for ants to gauge the similarity or dissimilarity between probability distributions. …”
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A Hybrid of Ant Colony Optimization Algorithm and Simulated Annealing for Classification Rules by Rizauddin, Saian

“…In the first proposed algorithm, SA is used to optimize the rule's discovery activity by an ant. …”
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Performance analysis of ant colony's algorithm: load-balancing in QoS-based wireless mesh networks routing by Moghanjoughi, Ayyoub Akbari, Khatun, Sabira, Mohd Ali, Borhanuddin, Raja Abdullah, Raja Syamsul Azmir

“…The design of the algorithm is based on: the specific self-organizing behavior of ant colonies, the shortest path discovery, and the related framework of ant colony optimization (ACO). …”
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Comparison between ant colony and genetic algorithm using traveling salesman problem by Abduljabbar, Zaid Ammen, Khalefa, Mustafa S., A. Jabar, Marzanah

“…The aim of this study is compare the effect of using two distributed algorithm which are ant colony as a Swarm intelligence algorithm and genetic algorithm. …”
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Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm by Al-Jumaili A.H.A., Muniyandi R.C., Hasan M.K., Singh M.J., Paw J.K.S., Al-Jumaily A.

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Optimizing large scale combinatorial problems using multiple ant colonies algorithm based on pheromone evaluation technique by Aljanaby, Alaa, Ku-Mahamud, Ku Ruhana, Md Norwawi, Norita

“…The new algorithm is based on the ant colony system and utilizes average and maximum pheromone evaluation mechanisms. …”
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Detecting canopy openings in logged-over forests: a multi-classifier analysis of PlanetScope imagery by Mawlidan, Nurmala, Ismail, Mohd Hasmadi, Gandaseca, Seca, ., Rahmawaty, Yaakub, Nur Faziera

“…Both SVM and OBIA surpassed the accuracy threshold, with SVM being the most effective in detecting and extracting canopy openings in dense forests. Results demonstrated the potential of PlanetSope imagery and advanced classification algorithms to detect canopy openings in logged-over forests. …”
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QoS based fair load-balancing: paradigm to IANRA routing algorithm for wireless networks (WNs) by Moghanjoughi, Ayyoub Akbari, Khatun, Sabira, Mohd Ali, Borhanuddin, Raja Abdullah, Raja Syamsul Azmir

“…The obtained results show that the efficiency of IANRA algorithm is better than AODV and AntNet or any other related algorithm. …”
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AntNet: a robust routing algorithm for data networks by Haseeb, Shariq, Sidek, Khairul Azami, Ismail, Ahmad Faris, Weng Kin, Lai, Yit Mei, Aw

“…AntNet is an innovative algorithm that may be used for data networks. …”
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Ant colony optimization algorithm for dynamic scheduling of jobs in computational grid by Ku-Mahamud, Ku Ruhana, Ramli, Razamin, Yusof, Yuhanis, Mohamed Din, Aniza, Mahmuddin, Massudi

“…Job scheduling problem is classified as an NP-hard problem.Such a problem can be solved only by using approximate algorithms such as heuristic and meta-heuristic algorithms.Among different optimization algorithms for job scheduling, ant colony system algorithm is a popular meta-heuristic algorithm which has the ability to solve different types of NP-hard problems.However, ant colony system algorithm has a deficiency in its heuristic function which affects the algorithm behavior in terms of finding the shortest connection between edges.This research focuses on a new heuristic function where information about recent ants’ discoveries has been considered.The new heuristic function has been integrated into the classical ant colony system algorithm.Furthermore, the enhanced algorithm has been implemented to solve the travelling salesman problem as well as in scheduling of jobs in computational grid.A simulator with dynamic environment feature to mimic real life application has been development to validate the proposed enhanced ant colony system algorithm. …”
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Performance Analysis of Swarm Intelligence-Based Routing Protocol for Mobile Ad Hoc Network and Wireless Mesh Networks by Moghanjoughi, Ayyoub Akbari

“…Among various works inspired by ant colonies, the Ant Colony Optimization (ACO) metaheuristic algorithms are the most successful and popular, e.g., AntNet, Multiple Ant Colony Optimization (MACO) and AntHocNet. …”
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DACS3:Embedding Individual Ant Behavior in Ant Colony System by Ali Othman, Zulaiha, Md Rais, Helmi, Hamdan, Abdul Razak

“…Their ability as a colony, to find paths to food sources has inspired the development of algorithms known as Ant Colony Systems (ACS). The principle of cooperation forms the backbone of such algorithms, commonly used to find solutions to problems such as the Traveling Salesman Problem (TSP). …”
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Ant colony algorithm for job scheduling in grid computing by Ku-Mahamud, Ku Ruhana, Abdul Nasir, Husna Jamal

“…Scheduling jobs to resources in grid computing is complicated due to the distributed and heterogeneous nature of the resources.Stagnation in grid computing system may occur when all jobs require or are assigned to the same resources.This will lead to resourccs having high workload and stagnation may occur if computational times of the processed jobs are high.This paper proposed an enhanced ant colony optimization algorithm for jobs and resources scheduling in grid computing.The proposed ant colony algorithm for job scheduling in the grid environment combines the techniques from Ant Colony System and Max - Min Ant System.The algorithm focuses on local pheromone trail update and the trail limit values. …”
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