Search Results - (( level classification using algorithm ) OR ( evolution optimization parallel algorithm ))

Optimization of extractive Automatic Text Summarization using Decomposition-based Multi-objective Differential Evolution and parallelization by Hazmi Wahab, Muhammad Hafizul

“…The central challenge in Automatic Text Summarization (ATS) is efficiently generating machine-generated text summaries through optimization algorithms, a critical component for systems dealing with textual information processing. …”
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PMT : opposition based learning technique for enhancing metaheuristic algorithms performance by Hammoudeh, S. Alamri

“…To evaluate the PMT’s performance and adaptability, the PMT was applied to four contemporary metaheuristic algorithms, Differential Evolution, Particle Swarm Optimization, Simulated Annealing, and Whale Optimization Algorithm, to solve 15 well-known benchmark functions as well as 2 real world problems based on the welded beam design and pressure vessel design. …”
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PMT: opposition-based learning technique for enhancing meta-heuristic performance by Alamri, Hammoudeh S., Kamal Z., Zamli

“…To evaluate the PMT's performance and adaptability, the PMT has been applied to four contemporary meta-heuristic algorithms, differential evolution (DE), particle swarm optimization (PSO), simulated annealing (SA), and whale optimization algorithm (WOA), to solve 15 well-known benchmark functions. …”
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OPTIMIZATION OF HYBRID-FUZZY CONTROLLER FOR SERVOMOTOR CONTROL USING A MODIFIED GENETIC ALGORITHM by WAHYUNGGORO, OYAS WAHYUNGGORO

“…In this thesis, a new optimization GA-based algorithm that emanates from modification of conventional GA to reduce the iterations number and the duration time, namely, semi-parallel operation genetic algorithm (SPOGA) is proposed. …”
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Application Of Genetic Algorithms For Robust Parameter Optimization by Belavendram, N.

“…Genetic algorithms (GA) are fairly recent in this respect but afford a novel method of parameter optimization. …”
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Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm by Hasan, Shafaatunnur, Tan, Swee Quo, Shamsuddin, Siti Mariyam, Sallehuddin, Roselina

“…Artificial Neural Network (ANN) is a new information processing system with large quantity of highly interconnected neurons or elements processing parallel to solve problems.Recently, evolutionary computation technique, Artificial Fish Swarm Algorithm (AFSA) is chosen to optimize global searching of ANN.In optimization process, each Artificial Fish (AF) represents a neural network with output of fitness value.The AFSA is used in this study to analyze its effectiveness in enhancing Multilayer Perceptron (MLP) learning compared to Particle Swarm Optimization (PSO) and Differential Evolution (DE) for classification problems.The comparative results indeed demonstrate that AFSA show its efficient, effective and stability in MLP learning.…”
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Multi-Class Multi-Level Classification of Mental Health Disorders Based on Textual Data from Social Media by Sutranggono, Abi Nizar, Sarno, Riyanarto, Ghozali, Imam

“…However, despite the large number of studies on the analysis of mental health disorders, the predominant algorithm in the existing literature is the Multi-Class Single-Level (MCSL) classification algorithm, which is often used for simple classification tasks involving a limited number of classes. …”
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Symmetric Key Size for Different Level of Information Classification by Ibrahim, Subariah, Maarof, Mohd. Aizaini

“…Therefore confidential information is normally protected by using cryptographic algorithms. In these algorithms, key is an important element since it is one of the parameters that determine the level of security that the algorithms can provide. …”
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Performance analysis of machine learning algorithms for classification of infection severity levels on rubber leaves by Mat Lazim, Siti Saripa Rabiah, Sulaiman, Zulkefly, Mat Nawi, Nazmi, Mohd Mustafah, Anas

“…The chlorophyll content of each leaf was measured using SPAD meter. Four classification algorithms investigated in this study were artificial neural network (ANN), support vector machine (SVM), knearest neighbour (kNN) and random forest (RF). …”
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Minimizing Classification Errors in Imbalanced Dataset Using Means of Sampling by Khan I., Ahmad A.R., Jabeur N., Mahdi M.N.

Data Mining Analysis Of Chronic Kidney Disease (CKD) Level by Mohd Harizi, Muhammad Hafizam Afiq

“…Adding the uncertain class the best accuracy obtained was 98.5% using the SMO algorithm. A predictive classification model that determines the accuracy for three classification classes was developed accordingly using the SMO algorithm.…”
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Automatic classification of medical x-ray images by Zare, M.R., Seng, W.C., Mueen, A.

“…Experimental results showed the classification performance obtained by exploiting LBP and BoW outperformed the other algorithms with respect to the image representation techniques used.…”
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Arabic text classification using hybrid feature selection method using chi-square binary artificial bee colony algorithm by Hijazi, Musab, Zeki, Akram M., Ismail, Amelia Ritahani

“…After that, the wrapper method, Artificial Bee Colony algorithm, is used as the second level where Naive Base is used as a fitness function. …”
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Classification of Diabetes Mellitus (DM) using Machine Learning Algorithms by Sirajun Noor, Noor Azmiya

“…The objective of this study is to perform DM classification using various machine learning algorithms using Weka as a tool. …”
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Multilayer Perceptron Neural Network In Classifying Gender Using Fingerprint Global Level Features by Siti Fairuz, Abdullah, Ahmad Fadzli Nizam, Abdul Rahman, Zuraida, Abal Abas, Wira Hidayat, Mohd Saad

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Autism Spectrum Disorder Classification Using Deep Learning by Abdulrazak Yahya, Saleh, Lim Huey, Chern

“…Several methods have been used to classify the ASD from non-ASD people. However, there is a need to explore more algorithms that can yield better classification performance. …”
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Jogging activity recognition using k-NN algorithm by Afifah Ismail

“…The k-NN algorithm is a simple and easy-to-implement supervised machine learning algorithm that can be used to solve both classification and regression problems. …”
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Image classification using two dimensional wavelet coefficients with parallel computing by Ong, Yew Fai

“…The low-level features such as edges, blobs, and ridges were extracted for grouping and classification. …”
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Fair bandwidth distribution marking and scheduling algorithm in network traffic classification by Al-Kharasani, Ameen Mohammed Abdulkarem

“…Additionally, the traffic are relying on the markers and scheduling algorithms to the service classes at the routers. The higher level priority agreements give a higher or equal probability than the lower level, this technique is perfect at a core router by scheduling algorithm. …”
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A Real time specific weed discrimination system using multi-Level wavelet decomposition by Siddiqi, M.H., Sulaiman, S., Faye, Ibrahima, Ahmad, I.

“…The developed algorithm was used for the real time specific weed discrimination employing multi-level wavelet decomposition. …”
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