Search Results - candidate ((((generation algorithm) OR (detection algorithm))) OR (optimization algorithm))

Static code analysis of permission-based features for android malware classification using apriori algorithm with particle swarm optimization by Adebayo, Olawale Surajudeen, Abdul Aziz, Normaziah

“…This paper presents a classification approach on android malware using candidate detectors generated from an unsupervised association rule of Apriori Algorithm. …”
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A generalized laser simulator algorithm for optimal path planning in constraints environment by Aisha, Muhammad

“…The results demonstrated that the proposed method could generate an optimal collision-free path. Moreover, the proposed algorithm result are compared to some common algorithms such as the A* algorithm, Probabilistic Road Map, RRT, Bi-directional RRT, and Laser Simulator algorithm to demonstrate its effectiveness. …”
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Improved Malware detection model with Apriori Association rule and particle swarm optimization by Adebayo, Olawale Surajudeen, Abdul Aziz, Normaziah

“…Particle swarm optimization (PSO) is used to optimize the random generation of candidate detectors and parameters associated with apriori algorithm (AA) for features selection. …”
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Android Malware classification using static code analysis and Apriori algorithm improved with particle swarm optimization by Adebayo, Olawale Surajudeen, Abdul Aziz, Normaziah

“…This paper presents a classification of android malware using candidate detectors generated from an unsupervised association rule of Apriori algorithm improved with particle swarm optimization to train three different supervised classifiers. …”
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Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things by Hadi, Ahmed Adnan

“…On the other hand, existing stream data learning models with limited labelling have many limitations. Most importantly, algorithms that suffer from a limited capability to adapt to the evolving nature of data generated from network traffic are called concept drift. …”
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Optimal Location And Sizing Of Distrubuted Generator Using PSO And GA Algorithms In Power Systems by Hassan, Ayat Saleh

“…In fact, there are several algorithms used for optimizing the size and finding the best location to install DG units in the power system. …”
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3D face candidate region detection using background subtraction / Zulfikri Paidi and Nurzaid Muhd Zain by Paidi, Zulfikri, Muhd Zain, Nurzaid

“…Our focus is to solve the first challenge in face registration, which is to detect and identify face region. From the experiment, it shows some promising results related to using background subtraction in face candidate region detection algorithm. …”
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Optimizing S-box generation based on the Adaptive Agent Heroes and Cowards Algorithm by Kamal Z., Zamli

“…This paper introduces a new variant of a metaheuristic algorithm based on Agent Heroes and Cowards Algorithm (AHC), called Adaptive Agent Heroes and Cowards Algorithm (AAHC). …”
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PMT : opposition based learning technique for enhancing metaheuristic algorithms performance by Hammoudeh, S. Alamri

“…Metaheuristic algorithms have shown promising performance in solving sophisticated real-world optimization problems. …”
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Enhanced Harris's Hawk algorithm for continuous multi-objective optimization problems by Yasear, Shaymah Akram

“…Harris’s hawk multi-objective optimizer (HHMO) algorithm is a MOSIbased algorithm that was developed based on the reference point approach. …”
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PMT: opposition-based learning technique for enhancing meta-heuristic performance by Alamri, Hammoudeh S., Kamal Z., Zamli

“…Meta-heuristic algorithms have shown promising performance in solving sophisticated real-world optimization problems. …”
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An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM) by Shamim, Akhtar

“…Therefore, in this study a new optimized variant of machine learning algorithms is presented. …”
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An improved grey wolf with whale algorithm for optimization functions by Asgher, Hafiz Maaz

“…The Grey Wolf Optimization (GWO) is a nature-inspired, meta-heuristic search optimization algorithm. …”
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Development of heuristic methods based on genetic algorithm (GA) for solving vehicle routing problem by Ismail, Zuhaimy, Nurhadi, Irhamah, Zainuddin, Zaitul Marlizawati

“…The computational complexity of most vehicle routing problem and moreover the intricate of stochastic VRP algorithm has made them an important candidate for solution using metaheuristics. …”
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Utilizing the roulette wheel based social network search algorithm for substitution box construction and optimization by Kamal Z., Zamli, Alhadawi, Hussam S., Fakhrud Din, .

“…This paper introduces a new variant of a recent metaheuristic algorithm based on the Social Network Search algorithm (SNS), which is called the Roulette Wheel Social Network Search algorithm (SNS). …”
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Optimization of an antenna array using genetic algorithms by Kiehbadroudinezhad, Shahideh, Noordin, Nor Kamariah, Sali, Aduwati, Zainal Abidin, Zamri

“…The genetic algorithm (GA) is an optimization solution for these kinds of problems that reconfigures the position of antennas to increase the u-v coverage plane or decrease the sidelobe levels (SLLs). …”
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Fuzzy Mixed Assembly Line Sequencing and Scheduling Optimization Model Using Multiobjective Dynamic Fuzzy GA by Zahari, Taha, Farzad, Tahriri, Siti Zawiah, Md Dawal

“…An improved genetic algorithm called fuzzy adaptive genetic algorithm (FAGA) is proposed in order to solve this optimization model. …”
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Crossover-first differential evolution for improved global optimization in non-uniform search landscapes by Teo, Jason Tze Wi, Mohd Hanafi Ahmad Hijazi, Hui, Keng Lau, Salmah Fattah, Aslina Baharum

“…The DE algorithm generates new candidate solutions by first conducting the mutation operation which is then followed by the crossover operation. …”
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An Efficient Genetic Algorithm for Large Scale Vehicle Routing Problem Subject to Precedence Constraints by Noraini, Mohd Razali

“…The conventional genetic algorithm procedure for TSP, with an order-based representation might generate invalid candidate solutions when precedence constraints are involved. …”
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Dingle's Model-based EEG Peak Detection using a Rule-based Classifier by Asrul, Adam, Norrima, Mokhtar, Marizan, Mubin, Zuwairie, Ibrahim, Mohd Ibrahim, Shapiai

“…In this study, the performances of four different peak models of time domain approach which are Dumpala's, Acir's, Liu's, and Dingle's peak models are evaluated for electroencephalogram (EEG) signal peak detection algorithm. The algorithm is developed into three stages: peak candidate detection, feature extraction, and classification. …”
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