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A case study of microarray breast cancer classification using machine learning algorithms with grid search cross validation by Mohd Ali, Nursabillilah, Besar, Rosli, Ab Aziz, Nor Azlina

“…In this work, simple machine learning methods are used to classify breast cancer microarray data to normal and relapse. …”
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A new variant of black hole algorithm based on multi population and levy flight for clustering problem by Haneen Abdul Wahab, Abdul Raheem

“…Black Hole (BH) optimization algorithm has been underlined as a solution for data clustering problems. …”
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Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves by Lia, Kamelia

“…In the next phase, the datasets are optimized using the Salp Swarm Algorithm (SSA), which improves classification accuracy. …”
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CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING by ISLAM, BADAR UL ISLAM

“…In the hybrid scheme, the initial parameters of the modified BP neural network are optimized by using the global search ability of genetic algorithm, improved by cat chaotic mapping to enrich its optimization capability. …”
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Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

“…Features selection process can be considered a problem of global combinatorial optimization in machine learning. Genetic algorithm GA had been adopted to perform features selection method; however, this method could not deliver an acceptable detection rate, lower accuracy, and higher false alarm rates. …”
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Automatic database of robust neural network forecasting / Saadi Ahmad Kamaruddin, Nor Azura Md. Ghani and Norazan Mohamed Ramli by Ahmad Kamaruddin, Saadi, Md. Ghani, Nor Azura, Mohamed Ramli, Norazan

“…The direct idea of making the conventional neural network learning algorithm more powerful towards outlying data is by replacing the mean square error (MSE) with a different symmetric and continuous cost function. …”
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Monotone Data Samples Do Not Always Produce Monotone Fuzzy If- Then Rules: Learning with Ad hoc and System Identification Methods by Chin, Ying Teh, Tay, Kai Meng, Chee, Peng Lim

“…Our analysis shows that even with multi-attribute monotone data, non-monotone fuzzy If- Then rules can be produced using an ad hoc method. The same observation can be made, empirically, using a system identification method, e.g., a derivative–based optimization method and the genetic algorithm. …”
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Deep learning-based item classification for retail automation by Ling, Ji Xiang

“…The CNN model was optimized for both accuracy and speed, incorporating regularization techniques such as dropout and batch normalization. …”
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Meta-cognitive Recurrent Recursive Kernel OS-ELM for concept drift handling by Liu, Zongying, Loo, Chu Kiong, Seera, Manjeevan

“…The recursive kernel method successfully replaces the normal kernel method in Recurrent Kernel Online Sequential Extreme Learning Machine with DDM (RKOS-ELM-DDM) and generates a fixed reservoir with optimized information in enhancing the forecasting performance. …”
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Mean of correlation method for optimization of affective states detection in children by Rusli, Nazreen, Sidek, Shahrul Na'im, Md Yusuf, Hazlina, Ishak, Nor Izzati

“…With the requirement of having the measuring device attached to the body approach, distraction of the subject normally masks the true affective states of the subject due to discomfort. …”
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Framework for pedestrian walking behaviour recognition to minimize road accident by Hashim Kareem, Zahraa

“…The results indicate the following: (1) From 262 samples, 66.80% and 48.10% of respondents use mobile phones for calling and chatting, respectively. (2) 263 samples of participants are obtained and analysed, and 90 features are extracted from each sample. (3) 100% classification accuracy are obtained for each class (normal walking, calling, chatting, and running) using the grid optimiser method in machine learning. (4) The precision of classification using Euclidean algorithm for normal walking and calling is 70%. …”
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Framework for pedestrian walking behaviour recognition to minimize road accident by Hashim Kareem, Zahraa

“…The results indicate the following: (1) From 262 samples, 66.80% and 48.10% of respondents use mobile phones for calling and chatting, respectively. (2) 263 samples of participants are obtained and analysed, and 90 features are extracted from each sample. (3) 100% classification accuracy are obtained for each class (normal walking, calling, chatting, and running) using the grid optimiser method in machine learning. (4) The precision of classification using Euclidean algorithm for normal walking and calling is 70%. …”
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Inversion of 2D and 3D DC resistivity imaging data for high contrast geophysical regions using artificial neural networks / Ahmad Neyamadpour by Neyamadpour, Ahmad

“…In order to study the effect of data pool formation in training the neural network, two methods have been used to generate the synthetic data. …”
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Malware Detection using Deep Learning (DL) by Chowdhury Sajadul Islam, Madihah Mohd Saudi, Nur Hafiza Zakaria, Muji Setiyo

Online system identification development based on recursive weighted least square neural networks of nonlinear hammerstein and wiener models. by Kwad, Ayad Mahmood

“…The parameters may vary as environmental conditions change. It requires big data and consumes a long time. This research introduces a developed method for online system identification based on the Hammerstein and Wiener nonlinear block-oriented structure with the artificial neural networks (NN) advantages and recursive weighted least squares algorithm for optimizing neural network learning in real-time. …”
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Algorithm enhancement for host-based intrusion detection system using discriminant analysis by Dahlan, Dahliyusmanto

“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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A study on advanced statistical analysis for network anomaly detection by Ngadi, Md. Asri, Idris, Mohd. Yazid, Abdullah, Abd. Hanan

“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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Experimental and AI-driven enhancements in gas-phase photocatalytic CO2 conversion over synthesized highly ordered anodic TiO2 nanotubes by Hossen, Md. Arif, Hasan, Md. Munirul, Ahmed, Yunus, Azrina, Abd Aziz, Nurashikin, Yaacof, Leong, Kah Hon

“…This study focuses on the prediction and optimization of CO2 conversion efficiency using machine learning (ML) approach over synthesized highly ordered TiO2 nanotube arrays (TNTAs) photocatalysts. …”
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Pengkelasan Sel Kanser Pangkal Rahim Kepada Sel Normal Dan Tidak Normal Menggunakan Analisis Pembezalayan Dan Rangkaian Neural by Saidin, Mohammad Norrish

“…The system is built to classify some certain data into two classes, which are normal or abnormal cells. …”
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Application of genetic algorithm methods to optimize flowshop sequencing problem by Mohd Fadil, Md Sairi

“…Genetic algorithm method was one of the methods that were widely used in solving optimization problem. …”
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