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Fault diagnosis of rotary kiln using SVM and binary ACO

Ouahab Kadri, Leila Hayet Mouss, Mohamed Djamel Mouss
2012 Journal of Mechanical Science and Technology  
The proposed algorithm is easily implemented and because of use of a simple filter in that, its computational complexity is very low.  ...  The algorithm can find a subset selection which is attained through the elimination of the features that produce noise or are strictly correlated with other already selected features.  ...  Acknowledgment The research has been generously supported by Batna University. The authors would like to express their sincere appreciation for all support provided.  ... 
doi:10.1007/s12206-011-1216-z fatcat:c4sazhtgbfdjhlzgittepgx5z4

Parallelization strategies for ant colony optimisation on GPUs

J. M. Cecilia, J. M. Garcia, M. Ujaldon, A. Nisbet, M. Amos
2011 2011 IEEE International Symposium on Parallel and Distributed Processing Workshops and Phd Forum  
Ant Colony Optimisation (ACO) is an effective population-based meta-heuristic for the solution of a wide variety of problems.  ...  However, up until now, the latter has always been implemented on the CPU. In this paper, we discuss several parallelisation strategies for both stages of the ACO algorithm on the GPU.  ...  ACKNOWLEDGEMENT This work was partially supported by a travel grant from HiPEAC, the European Network of Excellence on High Performance and Embedded Architecture and Compilation (http://www.hipeac.net)  ... 
doi:10.1109/ipdps.2011.170 dblp:conf/ipps/CeciliaGUNA11 fatcat:uzbw4nym5zbdxcxdndcpefevcy

A Master Slave Parallel Genetic Algorithm for Feature Selection in High Dimensional Datasets

2019 International journal of recent technology and engineering  
This paper describes the speed gains in parallel Master-Slave Genetic Algorithm and also discusses the theoretical analysis of optimal number of slaves required for an efficient master slave implementation  ...  Feature Selection in High Dimensional Datasets is a combinatorial problem as it selects the optimal subsets from N dimensional data having 2N possible subsets.  ...  Master-Slave GA can be implemented in an asynchronous manner provided the algorithm does not hold-up for the slow processor to conclude their allocated function evaluations and thus, there is no precise  ... 
doi:10.35940/ijrte.c4184.098319 fatcat:aqs3qv2r2bhprmafpw2smrj3ne

A comparative study of different machine learning methods for electricity prices forecasting of an electricity market

Elham Foruzan, Stephen D. Scott, Jeremy Lin
2015 2015 North American Power Symposium (NAPS)  
In addition, ant colony optimization (ACO) was used to reduce the feature space and give the best attribute subset for ANN model.  ...  Using ACO for feature selection significantly reduced the training time for ANN-based electricity price forecasting model while the results were almost as accurate as those from ANN model.  ...  The authors would like to thank Hossein Rabiee for helpfull discussions [15 , 16].  ... 
doi:10.1109/naps.2015.7335095 fatcat:avfx5nqplfaxhnwdddiymt34bi

Ant colony algorithm for text classification in multicore-multithread environment

Ahmad Nazmi Fadzal, Mazidah Puteh, Nurazzah Abd Rahman
2020 Indonesian Journal of Electrical Engineering and Computer Science  
Pheromone in ACO is the main concept used to solve the text classification problem.  ...  In regards to its role, pheromone value is changed depending on the solution finding that has been discovered at the pseudo random heuristic attempt in selecting path from text words.  ...  Maximum number of thread chosen is 16 because the time reduction values marginally decreasing as it exceed the maximum number of factory thread.  ... 
doi:10.11591/ijeecs.v18.i3.pp1359-1366 fatcat:gyf64layyrctnakeio6rtaqagi

Ant Colony Optimization: A Component-Wise Overview [chapter]

Manuel López-Ibáñez, Thomas Stützle, Marco Dorigo
2018 Handbook of Heuristics  
By configuring the parameters of the framework, one can combine features from various ACO algorithms in novel ways.  ...  In addition, the chapter introduces a software framework that unifies the implementation of these ACO algorithms for two example problems, the traveling salesman problem and the quadratic assignment problem  ...  We did not cover in this chapter research on the parallelization of ACO algorithms, which has the goal of either speeding-up the execution of a single run of an ACO algorithm or of increasing the quality  ... 
doi:10.1007/978-3-319-07124-4_21 fatcat:gfmhauijq5dqhkggdbrnkqguuy

Review on Dam and Reservoir Optimal Operation for Irrigation and Hydropower Energy Generation Utilizing Meta-Heuristic Algorithms

Kai Lun Chong, Sai Hin Lai, Ali Najah Ahmed, Wan Zurina Wan Jaafar, Ravipudi Venkata Rao, Mohsen Sherif, Ahmed Sefelnasr, Ahmed El-Shafie
2021 IEEE Access  
The problem of dam and reservoir optimization requires a fundamental shift of focus towards enhancing not only the problem formulation and decomposition but also the computational efficiency of MHAs.  ...  In engineering and scientific disciplines, there are extensive Optimization Application Problems (OAPs) such as economic dispatch, structural design, and water resources.  ...  Results have shown that in operating long-term planning rules, CA only requires a low number of function evaluations as compared to the high number of function evaluations by the GA, PSO, and ACO algorithms  ... 
doi:10.1109/access.2021.3054424 fatcat:hsbnjy5a3bhhpawfjkuzctvxly

ACO-SA: ENHANCED OPTIMIZATION FOR TSP

Sudeepta Thukral
2017 International Journal of Advanced Research in Computer Science  
The results exemplify that both the average cost and number of iteration to the best known solution of proposed method are better than existing methods.  ...  Swarm intelligence (SI) algorithms be capable of efficiently achieve best tours with minimum lengths. ACO is type of probability technology use to get optimal path in the graph.  ...  First, candidate set approach is implemented to fast convergence speed.  ... 
doi:10.26483/ijarcs.v8i7.4244 fatcat:djcechfz35et3f6j3633qdns5e

Improving KNN by Gases Brownian Motion Optimization Algorithm to Breast Cancer Detection

Majid Abdolrazzagh-Nezhad, Shokooh Pour Mahyabadi, Ali Ebrahimpoor
2020 Data Science: Journal of Computing and Applied Informatics  
To achieve to this aim, each gas molecule contains the information such as a selected subset of features to apply the KNN and k value.  ...  to the size of the data and sample selected for training.  ...  These objectives are composed by designing the structure of a molecule in terms of one bit for a value of K and assuming n features, the number of n binary bits representing the subset of the selected  ... 
doi:10.32734/jocai.v4.i1-3619 fatcat:lbeixadtebh77nrhp2rfohojp4

A Review of the Modification Strategies of the Nature Inspired Algorithms for Feature Selection Problem

Ruba Abu Abu Khurma, Ibrahim Aljarah, Ahmad Sharieh, Mohamed Abd Abd Elaziz, Robertas Damaševičius, Tomas Krilavičius
2022 Mathematics  
We identified and performed a thorough literature review in three main streams of research lines: Feature selection problem, optimization algorithms, particularly, meta-heuristic algorithms, and modifications  ...  applied to NIAs to tackle the FS problem.  ...  Conflicts of Interest: All authors declare that they have no conflict of interest.  ... 
doi:10.3390/math10030464 fatcat:sjg667gilzfktokxxjwdg52jbm

Distribution Feeder Reconfiguration for Loss Minimization Based on Modified Honey Bee Mating Optimization Algorithm

Javad Olamaei, Taher Niknam, Sirous Badali Arefi
2012 Energy Procedia  
Because of the fact that the objectives are different and no commensurable, it is difficult to solve the problem by conventional approaches that may optimize a single objective.  ...  This paper describes the full algorithm to Objective functions paid, The results of simulations on a 32 bus distribution system is given and shown high accuracy and optimize the proposed algorithm in power  ...  This feature will limit the unnecessary objective function evaluation for heuristic functions with non-significant contribution in solution improvements.  ... 
doi:10.1016/j.egypro.2011.12.934 fatcat:eepnkzvlvzf7bcip6jm2uepdtu

Hybrid Ant Colony Optimization and Genetic Algorithm for Rule Induction

Hayder Naser Khraibet AL-Behadili, Ku Ruhana Ku-Mahamud, Rafid Sagban
2020 Journal of Computer Science  
In this study, a hybrid rule-based classifier namely, ant colony optimization/genetic algorithm ACO/GA is introduced to improve the classification accuracy of Ant-Miner classifier by using GA.  ...  The performance of the proposed classifier was tested against other existing hybrid ant-mining classification algorithms namely, ACO/SA and ACO/PSO2 using classification accuracy, the number of discovered  ...  The corresponding author confirms that all of the other authors have read and approved the manuscript and there are no ethical issues involved.  ... 
doi:10.3844/jcssp.2020.1019.1028 fatcat:52ur554w2zanva4vqxzygynr4u

Evolutionary Algorithms for Real Time Engineering Problems: A Comprehensive Review

Devineni Gireesh Kumar, Aman Ganesh, Neerudi Bhoopal, Sankaranarayanan Saravanan, Madala Prameela, Dsnmrao, Idamakanti Kasireddy
2021 Ingénierie des Systèmes d'Information  
For selected optimization strategies, the process of formulating the objective function/stiffness function for a minimal issue exists.  ...  This paper presents a variety of contemporary optimization techniques inspired by the real life in nature.  ...  PSO-TS hybrid algorithm The Nonlinear Simplex Method (NSM) implemented into PSO to speed up its transition [42] .  ... 
doi:10.18280/isi.260205 fatcat:zyx24isi3jbjfppjwgalqtgrc4

Ants can solve constraint satisfaction problems

C. Solnon
2002 IEEE Transactions on Evolutionary Computation  
In this paper, we describe a new incomplete approach for solving constraint satisfaction problems (CSPs) based on the ant colony optimization (ACO) metaheuristic.  ...  The idea is to use artificial ants to keep track of promising areas of the search space by laying trails of pheromone.  ...  This shows that preprocessing speeds up the solution process. A.  ... 
doi:10.1109/tevc.2002.802449 fatcat:rptpgsagd5cjnogbgcl5c5eam4

Building a multi-signal based defect prediction system for a friction stir welding process

T.W. Liao, J. Roberts, M.A. Wahab, A.M. Okeil
2019 Procedia Manufacturing  
Extracted features were then pooled together and selected using ACO in the process of building model for testing.  ...  Extracted features were then pooled together and selected using ACO in the process of building model for testing.  ...  Acknowledgements Authors gratefully acknowledge the financial support received from NASA through the NASA-SLS Grant # NNM13AA02G, the LaSpace (GSRA), the Proof-of-Concept/Prototyping Initiative (PoC/P)  ... 
doi:10.1016/j.promfg.2020.01.089 fatcat:wajxafjedbg5besku7k36ydfku
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