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A class skew-insensitive ACO-based decision tree algorithm for imbalanced data sets by Mohd Razali, Muhamad Hasbullah, Saian, Rizauddin, Yap, Bee Wah, Ku-Mahamud, Ku Ruhana

“…This condition impeded the entropy-based heuristic of existing ATM algorithm to develop effective decision boundaries due to its biasness towards the dominant class. …”
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Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

“…Evolutionary computation is the name given to a collection of algorithms based on the evolution of a population toward a solution of a certain problem. …”
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Students’ attitude towards video-based learning: machine learning analysis with rapid software / Abdullah Sani Abd Rahman ... [et al.] by Abd Rahman, Abdullah Sani, Meutia, Rita, Hamid, Yusnaliza, Abdul Rahman, Rahayu

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Non-Distortion-Specific No-Reference Image Quality Assessment:A Survey by Abdul Manap, Redzuan, Shao, Ling

“…Over the last two decades,there has been a surge of interest in the research of image quality assessment due to its wide applicability to many domains.In general,the aim of image quality assessment algorithms is to evaluate the perceptual quality of an image using an objective index which should be highly consistent with the human subjective index.The objective image quality assessment algorithms can be classified into three main classes: full-reference,reduced-reference,and no-reference.While full-reference and reduced-reference algorithms require full information or partial information of the reference image respectively,no reference information is required for no-reference algorithms.Consequently,a no-reference (or blind) image quality assessment algorithm is highly preferred in cases where the availability of any reference information is implausible.In this paper,a survey of the recent no-reference image quality algorithms,specifically for non-distortion-specific cases,is provided in the first half of this paper.Two major approaches in designing the non-distortion-specific no-reference algorithms,namely natural scene statistics-based and learning-based,are studied.In the second half of this paper,their performance and limitations are discussed before current research trends addressing the limitations are presented.Finally,possible future research directions are proposed towards the end of this paper.…”
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Design of a pattern classification system using extreme learning machine by Sakthivel Thangavelu

Design of a pattern classification system using extreme learning machine by Sakthivel Thangavelu

Simulated Kalman Filter with modified measurement, substitution mutation and hamming distance calculation for solving traveling salesman problem by Suhazri Amrin, Rahmad, Zuwairie, Ibrahim, Zulkifli, Md. Yusof

“…We reviewed 57 SKF papers. 16 of them on fundamental improvements, 9 on extension of the algorithm to discrete problems and 25 on their applications. …”
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A framework of modified adaptive neuro-fuzzy inference engine by Hossen, Md. Jakir

“…The Takagi-Sugeno-Kang (TSK) type fuzzy inference system was chosen and constructed by an automatic generation of clusters as well as membership functions and minimal rules through the use of hybrid fuzzy clustering and the modified apriori algorithms respectively. The developed TSK type fuzzy inference engine is called modified adaptive fuzzy inference engine (MAFIE) and its parameters were then adjusted by the hybrid learning algorithm using adaptive neural network architecture towards improved performance which is called MANFIE. …”
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A Stacked Ensemble Deep Learning Approach For Imbalanced Multi-class Water Quality Index Prediction by Wen Yee Wong, Khairunnisa Hasikin, Anis Salwa Mohd Khairuddin, Sarah Abdul Razak, Hanee Farzana Hizaddin, Mohd Istajib Mokhtar, Muhammad Mokhzaini Azizan

State of Charge Estimation for Lithium-Ion Batteries Using Model-Based and Data-Driven Methods: A Review by How D.N.T., Hannan M.A., Hossain Lipu M.S., Ker P.J.

Design of Predictive Model for TCM Tongue Diagnosis In Malaysia Using Machine Learning by Koe, Jia Chi

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Mental stress classification based on selected electroencephalography channels using correlation coefficient of Hjorth parameters by Hag, Ala, Al-Shargie, Fares, Handayani, Dini Oktarina Dwi, Asadi, Houshyar

“…Leveraging features from the time, frequency, and time–frequency domains of these channels, and employing machine learning algorithms, notably RLDA, SVM, and KNN, our approach achieved a remarkable accuracy of 81.56% with the SVM algorithm outperforming existing methodologies. …”
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Deep plant: A deep learning approach for plant classification / Lee Sue Han by Lee , Sue Han

“…In summary, the collective impact of the above contributions have constituted to achieve a more practical and feasible framework towards the applications of plant identification. …”
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Fuzzy logic inverter controller in photovoltaic applications: Issues and recommendations by Hannan M.A., Ghani Z.A., Hoque M.M., Ker P.J., Hussain A., Mohamed A.

Development of an artificial neural network algorithm for predicting the cutting force in end milling of Inconel 718 alloy by Hossain, Ishtiaq, Amin, A. K. M. Nurul, Patwari, Muhammed Anayet Ullah

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Automatic parking management system and parking fee collection based on number plate recognition by Rashid, Muhammad Mahbubur, A., Musa, M, Ataur Rahman, A, Farahana, A., Farhana

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LINGUISTIC FUZZY MODELING IN LASER MACHINING QUALITY EVALUATION by Sivarao, Subramonian

“…The aim of this scientific research is to design knowledge based linguistic rules, algorithm, architecture & learning ability and further develop fuzzy model for laser machining kerf edge quality prediction. …”
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AI-Based Drug Design: Revolutionizing Drug Discovery through in Silico Analysis by Yamini Priya, Deepthimahanthi, Prakash, Balu, Wong, Ling Shing, Kumar, Krishnan, J., Manjunathan, K., Ashokkumar, M., Jayanthi, M., Suganthi, G., Abirami

“…The convergence of artificial intelligence (AI) and drug design has catalyzed a tectonic shift within the pharmaceutical arena, illuminating a new path towards rapid and efficient drug discovery. This review embarks on an odyssey through the transformative landscape of AI-based drug design, delving into its multifaceted applications and profound implications. …”
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Digital assistant for workspace apps by See, Ling Xuan

“…The proposed system will be achieved by applying machine learning to train the digital assistant model for it can study and execute every Teams’ function or the function combinations and allow user customization on its steps to complete certain task. …”
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Software agent as an effective tool for managing the Internet of thing data complexity by Mustafa, M.B., Yusoof, M.A.M.

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