Search Results - candidate ((((generation algorithm) OR (selection algorithm))) OR (detection 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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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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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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Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things by Hadi, Ahmed Adnan

“…Here, the memory consumption can be reduced by enabling a feature selection algorithm that excludes nonrelevant features and preserves the relevant ones. the algorithm is developed based on the variable length of the PSO. …”
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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

“…This research designed an anomaly-based detection, by adopting the modified Cuckoo Search Algorithm (CSA), called Mutation Cuckoo Fuzzy (MCF) for feature selection and Evolutionary Neural Network (ENN) for classification. …”
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Automated face localization and facial features detection using geometric information by Chai, Tong Yuen, Mohd Rizon, Mohamed Juhari, Prof. Dr., Karthigayan, M., Sugisaka, M., Hazry, Desa, Dr., Ibrahim, Z.

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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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Research on the construction of an efficient and lightweight online detection method for tiny surface defects through model compression and knowledge distillation by Chen, Qipeng, Xiong, Qiaoqiao, Huang, Haisong, Tang, Saihong, Liu, Zhenghong

“…The K-means++ clustering algorithm generates candidate bounding boxes, adapting to defects of different sizes and selecting finer features earlier. …”
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Temporal video segmentation using squared form of Krawtchouk-Tchebichef moments by Abdulhussain, Sadiq H.

“…In the proposed TVS, a modified candidate segment selection technique is initially employed to determine the candidate segments from the entire video. …”
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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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Improving the efficiency of clustering algorithm for duplicates detection by Emran, Nurul Akmar, Abdul Rahim, Abdulrazzak Ali Mohamed, Kamal Baharin, Safiza Suhana, Othman, Zahriah, Salem, Awsan Thabet, Abd Aziz, Maslita, Md. Bohari, Nor Mas Aina, Abdullah, Noraswaliza

“…Two datasets (compact disc database (CDDB) and MusicBrainz) were used to test duplicates detection algorithms. The duplicates detection toolkit(DuDe) was used as a benchmark for the proposed method. …”
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Automatic selection of initial points for exploratory vessel tracing in fluoroscopic images by Boroujeni, Farsad Zamani, O. K. Rahmat, Rahmita Wirza, Mustapha, Norwati, Affendey, Lilly Suriani, Maskon, Oteh

“…This paper presents a new method for efficient selection of initial points for exploratory tracing algorithms. …”
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PMT : opposition based learning technique for enhancing metaheuristic algorithms performance by Hammoudeh, S. Alamri

“…Like existing OBL-based approaches, the PMT generates new potential solutions based on the currently selected candidate. …”
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An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM) by Shamim, Akhtar

“…The deliverable of this phase is the selection of the best candidate of machine learning algorithm for university campus energy load prediction. …”
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PMT: opposition-based learning technique for enhancing meta-heuristic performance by Alamri, Hammoudeh S., Kamal Z., Zamli

“…Like existing OBL-based approaches, the PMT generates new potential solutions based on the currently selected candidate. …”
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Cluster head selection using fuzzy logic and chaotic based genetic algorithm in wireless sensor network by Karimi, Abbas, Abedini, S. M., Zarafshan, Faraneh, Syed Mohamed, Syed Abdul Rahman Al-Haddad

“…In other words, fuzzy logic is proposed based on three variables- energy, density and centrality-to introduce the best nodes to base station as cluster head candidate. Then, the number and place of cluster heads are determined in base station by using genetic algorithm based on chaotic. …”
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Enhanced Harris's Hawk algorithm for continuous multi-objective optimization problems by Yasear, Shaymah Akram

“…The algorithm includes (i) a population update strategy which improves the movement of hawks in the search space, (ii) a parameter adjusting strategy to control the transition between exploration and exploitation, and (iii) a population generating method in producing the initial candidate solutions. …”
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Fast shot boundary detection based on separable moments and support vector machine by Idan, Zinah N., Abdulhussain, Sadiq H., Mahmmod, Basheera M., Al-Utaibi, Khaled A., Syed Abdul Rahman Al-, Syed Abdul Rahman Al-Hadad, Sait, Sadiq M.

“…The proposed SBD framework is based on the concept of candidate segment selection with frame active area and separable moments. …”
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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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