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Automatic email classification system / Phang Siew Ting by Phang , Siew Ting

“…Automatic Email Classification System is an email reader tool that implements machine learning algorithm in email classification, manipulated by a Graphical User Interface. …”
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A hybrid algorithm based on artificial bee colony and artificial rabbits optimization for solving economic dispatch problem by Lee, Wei Wen, Hashim, Mohd Ruzaini

“…Hence, a hybrid optimization algorithm called Artificial Bee Rabbit Optimization (ABRO) is proposed in this paper. …”
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Artificial bee colony algorithm with proposed discrete nearest neighborhood algorithm for discrete optimization problems by Rahimi, Amir Masoud, Ramezani-Khansari, Ehsan

“…To reduce the optimization time of the tours created by the artificial bee colony algorithm, the fixed-radius near neighbor 2-opt algorithm was used as well. …”
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Automatic topic-based web page classification using deep learning by Siti Hawa, Apandi, Jamaludin, Sallim, Rozlina, Mohamed, Norkhairi, Ahmad

“…However, there is lack of study that review classification of web pages using deep learning. In this study, the automatic topic-based classification of web pages utilising deep learning that has been proposed by many key researchers are reviewed. …”
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Automatic Topic-Based Web Page Classification Using Deep Learning by Siti Hawa, Apandi, Jamaludin, Sallim, Rozlina, Mohamed, Norkhairi, Ahmad

“…However, there is lack of study that review classification of web pages using deep learning. In this study, the automatic topic-based classification of web pages utilising deep learning that has been proposed by many key researchers are reviewed. …”
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The use of SOM for fingerprint classification by Turky A.M., Ahmad M.S.

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The efficacy of deep learning algorithm in classifying chilli plant growth stages by Muammar Rozilan, Danial Mirza, Hanafi, Marsyita, Ali, Roslizah, Razak, Mohd Adib, Cui, Hairu

“…The demand in this field has created various opportunities, especially for automatic classification using deep learning methods. …”
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Local search manoeuvres recruitment in the bees algorithm by Muhamad, Zaidi, Mahmuddin, Massudi, Nasrudin, Mohammad Faidzul, Sahran, Shahnorbanun

“…The Bees Algorithm (BA) was created specifically by mimicking the foraging behavior of foraging bees in searching for food sources.During the searching, the original BA ignores the possibilities of the recruits being lost during the flying.The BA algorithm can become closer to the nature foraging behavior of bees by taking account of this phenomenon.This paper proposes an enhanced BA which adds a neighbourhood search parameter which we called as the Local Search Manoeuvres (LSM) recruitment factor.The parameter controls the possibilities of a bee extends its neighbourhood searching area in certain direction.The aim of LSM recruitment is to decrease the number of searching iteration in solving optimization problems that have high dimensions.The experiment results on several benchmark functions show that the BA with LSM performs better compared to the one with basic recruitment.…”
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Breast cancer disease classification using fuzzy-ID3 algorithm with FUZZYDBD method: automatic fuzzy database definition by Nur Farahaina, Idris, Mohd Arfian, Ismail

“…FID3 algorithm combined the fuzzy system and decision tree techniques with ID3 algorithm as the decision tree learning. …”
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The design and applications of the african buffalo algorithm for general optimization problems by Odili, Julius Beneoluchi

“…Some of the successfully designed stochastic algorithms include Simulated Annealing, Genetic Algorithm, Ant Colony Optimization, Particle Swarm Optimization, Bee Colony Optimization, Artificial Bee Colony Optimization, Firefly Optimization etc. …”
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Data Analysis using Particle Swarm Optimization Algorithm by Tai, Zu Jie

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RLMD-PA: A Reinforcement Learning-Based Myocarditis Diagnosis Combined with a Population-Based Algorithm for Pretraining Weights by Seyed Vahid Moravvej, Roohallah Alizadehsani, Sadia Khanam, Zahra Sobhaninia, Afshin Shoeibi, Fahime Khozeimeh, Zahra Alizadeh Sani, Ru-San Tan, Abbas Khosravi, Saeid Nahavandi, Nahrizul Adib Kadri, N. Arunkumar, U.Rajendra Acharya, Muhammad Mokhzaini Azizan

Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images by Adil Humayun, Khan

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Classification of JPEG files by using extreme learning machine by Ali, Rabei Raad, Mohamad, Kamaruddin Malik, Jamel, Sapiee, Ahmad Khalid, Shamsul Kamal

“…The algorithm automatically classifies the files based on evaluation measures of three methods Entropy, Byte Frequency Distribution and Rate of Change. …”
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Development of lung cancer prediction system using meta-heuristic optimized deep learning model by Mohamed Shakeel, Pethuraj

“…Finally, the classification is implemented using an ensemble classifier, deep learning instantaneously trained a neural network and an Autoencoder-based Recurrent Neural Network (ARNN) classification algorithm. …”
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Machine Learning-based Classification Of Termite Genera by Sundresan A/L Perumal, Homathevi Rahman, Valliappan Raman, Subramanian Raja Nagendran, Bala Saatvik Thanigai Arasu, Deepakkumar Senthil Kumar, Roghan Raja

Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

“…This learning algorithm represents an automatic generation of membership functions and rules from the data. …”
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A study on feature selection and classification techniques for automatic genre classification of traditional Malay music by Doraisamy, Shyamala, Golzari, Shahram, Mohd. Norowi, Noris, Sulaiman, Md. Nasir, Udzir, Nur Izura

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Fusion of moment invariant method and deep learning algorithm for COVID-19 classification by Ervin Gubin Moung, Chong, Joon Hou, Maisarah Mohd Sufian, Mohd Hanafi Ahmad Hijazi, Jamal Ahmad Dargham, Sigeru Omatu

“…This paper proposes a fusion of a moment invariant (MI) method and a DL algorithm for feature extraction to address the instabilities in the existing COVID-19 classification models. …”
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A Truly Online Learning Algorithm using Hybrid Fuzzy ARTMAP and Online Extreme Learning Machine for Pattern Classification by Wong, S.Y., Yap, K.S., Yap, H.J., Tan, S.C.

“…The idea of developing FAM-OELM is motivated by the ELM concept proposed by Huang et al., for being an efficient learning algorithm that provides better generalization performance at a much faster learning speed. …”
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