Search Results - (( severity classification using algorithm ) OR ( based optimization method algorithm ))

Gender classification on skeletal remains: efficiency of metaheuristic algorithm method and optimized back propagation neural network by Hairuddin, Nurul Liyana, Yusuf, Lizawati Mi, Othman, Mohd Shahizan

“…Thus, this paper proposed metaheuristic algorithms such as Particle Swarm Optimization, Ant Colony Algorithm and Harmony Search Algorithm based feature selection to identify the most significant features of skeleton remains. …”
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Enhancing Classification Algorithms with Metaheuristic Technique by Cokro, Nurwinto, Tri Basuki, Kurniawan, Misinem, ., Tata, Sutabri, Yesi Novaria, Kunang

“…For this reason, in this research,several auxiliary algorithms are introduced to improve the performance of the classification algorithm, namely the meta-heuristic algorithm. …”
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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

“…However, supervised learning technique has limitations for malware classification task. 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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Optimization of k-Nearest Neighbour to categorize Indonesian’s news articles by Ihsan, Afdhalul, Rainarli, Ednawati

“…The way to solve this problem is to conduct the feature selection process. There are several filter-based feature selection methods; some are Chi-Square, Information Gain, Genetic Algorithm, and Particle Swarm Optimization (PSO). …”
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Software defect prediction framework based on hybrid metaheuristic optimization methods by Wahono, Romi Satria

“…For the purpose of this study, ten classification algorithms have been selected. The selection aims at achieving a balance between established classification algorithms used in software defect prediction. …”
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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

“…Several machine learning techniques based on supervised learning have been adopted in the classification of malware. …”
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Finite impulse response optimizers for solving optimization problems by Ab Rahman, Tasiransurini

“…The classification of estimation-based metaheuristic algorithms has been introduced for solving optimization problems. …”
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Finite impulse response optimizers for solving optimization problems by Tasiransurini, Ab Rahman

“…The classification of estimation-based metaheuristic algorithms has been introduced for solving optimization problems. …”
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Opposition Based Competitive Grey Wolf Optimizer For EMG Feature Selection by Too, Jing Wei, Abdullah, Abdul Rahim

“…Four state-of-the-art algorithms include particle swarm optimization, flower pollination algorithm, butterfly optimization algorithm, and CBGWO are used to examine the effectiveness of proposed methods in feature selection. …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

“…Feature subset selection and classifier ensemble learning are familiar techniques with high ability to optimize above problems. Recently, various techniques based on different algorithms have been developed. …”
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Fair bandwidth distribution marking and scheduling algorithm in network traffic classification by Al-Kharasani, Ameen Mohammed Abdulkarem

“…Finally, propose a new method of obtaining optimal parameters dropping functions for Random Early Detection (RED) algorithm. …”
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Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals by Too, Jing Wei

“…In this regard, this thesis proposes five FS methods for efficient EMG signals classification. The first method is the Binary Tree Growth Algorithm (BTGA), which implements a hyperbolic tangent function to convert the Tree Growth Algorithm into the binary version. …”
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Hybrid performance measures and mixed evaluation method for data classification problems by Hossin, Mohammad

“…This study investigates two different issues of performance measure in data classification problem. First, this study examines the use of accuracy measure as a discriminator for building an optimized Prototype Selection (PS) algorithm. …”
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Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms by Alswaitti, Mohammed Y. T.

“…Nature-inspired optimization-based clustering techniques are powerful, robust and more sophisticated than the conventional clustering methods due to their stochastic and heuristic characteristics. …”
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A modified weighted support vector machine (WSVM) to reduce noise data in classification problem by Mohd Dzulkifli, Syarizul Amri

“…When noise exists in training data, the decision boundary of SVM would deviate from the optimal hyperplane severely. To overcome SVM drawback for noise data problem, WSVM using KPCM algorithm was used but WSVM using kernel-based learning algorithm such as KPCM algorithm suffer from training complexity, expensive computation time and storage memory when noise data contaminate training data. …”
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A modified weighted support vector machine (WSVM) to reduce noise data in classification problem by Mohd Dzulkifli, Syarizul Amri

“…When noise exists in training data, the decision boundary of SVM would deviate from the optimal hyperplane severely. To overcome SVM drawback for noise data problem, WSVM using KPCM algorithm was used but WSVM using kernel-based learning algorithm such as KPCM algorithm suffer from training complexity, expensive computation time and storage memory when noise data contaminate training data. …”
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Optimization and discretization of dragonfly algorithm for solving continuous and discrete optimization problems by Bibi Amirah Shafaa, Emambocus

“…The trained network is then applied to benchmark classification problems. Based on the experimental results, the optimized DA algorithm is a much better training algorithm for ANNs as compared to the usual gradient-descent backpropagation algorithm since the resultant ANNs trained by the optimized DA achieve higher accuracy. …”
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Optimized feature construction methods for data summarizations of relational data by Sze, Florence Sia Fui

“…The proposed framework involves the application of genetic algorithm which incorporates several feature scoring measures to optimize the process of feature construction. …”
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Automated plant classification system using a hybrid of shape and color features of the leaf by Hamid, Laith Emad

“…Automated plant leaf classification is a computerized approach that employs computer vision and machine learning algorithms to identify a plant based on the features of its leaf. …”
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Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi by Atefi, Kayvan

“…In fact a data clustering method is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on our proposed algorithm; which is Enhanced Binary Particle swarm Optimization (EBPSO), (ii) To mine data using various data chunks (windows) and overcome a failure of single clustering. …”
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