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

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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An efficient anomaly intrusion detection method with feature selection and evolutionary neural network by Sarvari, Samira, Mohd Sani, Nor Fazlida, Mohd Hanapi, Zurina, Abdullah @ Selimun, Mohd Taufik

“…The proposed search algorithm uses mutation to more accurately examine the search space, to allow candidates to escape local minima. …”
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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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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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PMT : opposition based learning technique for enhancing metaheuristic algorithms performance by Hammoudeh, S. Alamri

“…Experimentally, the PMT shows promising results by accelerating the convergence rate against the original algorithms with the same number of fitness evaluations comparing to the original metaheuristic algorithms in benchmark functions and real-world optimization problems.…”
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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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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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Optimizing S-box generation based on the Adaptive Agent Heroes and Cowards Algorithm by Kamal Z., Zamli

“…The main feature of AAHC is the fact that the algorithm allows adaptive assignment of its population agents into cowards and heroes based on the exponential controlling functions. …”
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Optimal Location And Sizing Of Distrubuted Generator Using PSO And GA Algorithms In Power Systems by Hassan, Ayat Saleh

“…The multi-objective function, which represents the summation of product three indices by corresponding weights was utilized to identify the candidate buses to reduce the search space of the algorithm. …”
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An improved grey wolf with whale algorithm for optimization functions by Asgher, Hafiz Maaz

“…The performance of the proposed algorithm is tested and evaluated on five benchmarked unimodal and five multimodal functions. …”
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PMT: opposition-based learning technique for enhancing meta-heuristic performance by Alamri, Hammoudeh S., Kamal Z., Zamli

“…Unlike existing OBL-based techniques, the PMT generates more than one candidate in multiple solution-space directions. …”
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Levy slime mould algorithm for solving numerical and engineering optimization problems by J. J., Jui, M. A., Ahmad, M. I. M., Rashid

“…We took advantage of the Levy flight, which solved the local optima problem and improved traditional SMA efficiency. The proposed LSMA algorithm performance was evaluated using 23 well-known benchmark test functions, namely unimodal benchmark functions, multimodal benchmark functions, and fixed-dimension multimodal benchmark functions, as well as compared with the traditional SMA. …”
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Hash function of finalist SHA-3: analysis study by Alshaikhli, Imad Fakhri Taha, Alahmad, Mohammad A., Munthir, Khansaa

“…Thus, for this reason the paper addresses the comparative and analysis study of the finalist SHA-3 candidates in: complexity of security, design and structure, as well as performance and cost, to measure the robustness of the algorithms in this area, through the Fundamentals Security Measurement Factors of Hash Function (FSMFHF) of Secure Hash Algorithm (SHA). …”
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Informative top-k class associative rule for cancer biomarker discovery on microarray data by Ong, Huey Fang, Mustapha, Norwati, Hamdan, Hazlina, Rosli, Rozita, Mustapha, Aida

“…This paper proposes an informative top-k class associative rule (iTCAR) method in an integrative framework for identifying candidate genes of specific cancers. iTCAR introduces an enhanced associative classification algorithm that integrates microarray data with biological information from gene ontology, KEGG pathways, and protein-protein interactions to generate informative class associative rules. …”
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Informative top-k class associative rule for cancer biomarker discovery on microarray data by Ong, Huey Fang, Mustapha, Norwati, Hamdan, Hazlina, Rosli, Rozita, Mustapha, Aida

“…This paper proposes an informative top-k class associative rule ( i TCAR) method in an integrative framework for identifying candidate genes of specific cancers. i TCAR introduces an enhanced associative classification algorithm that integrates microarray data with biological informa- tion from gene ontology, KEGG pathways, and protein-protein interactions to generate informative class associative rules. …”
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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.

“…Data vectors are generated based on the time needed, sequential and parallel candidate feature data are obtained, and the data rate is combined. …”

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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An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM) by Shamim, Akhtar

“…This study recommends a selection trade-off as the function of prediction efficiency and efficacy of the algorithm. …”
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Defect green coffee bean detection using image recognition and supervised learning by Shafian Izan Sofian

“…Therefore, in this research project, the process will be conducted by using an image classifier with the model of a machine learning algorithm which the candidates comprise of Support Vector Machine, k-Nearest Neighbour and Decision Tree. k-nearest neighbour has the highest F1-score (0.51) than the other two algorithms (Support Vector Machine: 0.50, and Decision Tree: 0.48). …”
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A new variant of black hole algorithm based on multi population and levy flight for clustering problem by Haneen Abdul Wahab, Abdul Raheem

“…The second modification is the multiple population BH that is proposed as a generalization to the BH algorithm, in which the algorithm was not reliant upon the best solution but rather on a set of best solutions generated, called “MBH”. …”
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