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A Theoretical Framework for Big Data Analytics Based on Computational Intelligent Algorithms with the Potential to Reduce Energy Consumption by Chiroma, H., Abdullahi, U.A., Hashem, I.A.T., Saadi, Y., Al-Dabbagh, R.D., Ahmad, M.M., Dada, G.E., Danjuma, S., Maitama, J.Z., Abubakar, A., Abdulhamid, S.�M.

“…The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. …”
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A Theoretical Framework for Big Data Analytics Based on Computational Intelligent Algorithms with the Potential to Reduce Energy Consumption by Chiroma, H., Abdullahi, U.A., Hashem, I.A.T., Saadi, Y., Al-Dabbagh, R.D., Ahmad, M.M., Dada, G.E., Danjuma, S., Maitama, J.Z., Abubakar, A., Abdulhamid, S.�M.

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A Theoretical Framework for Big Data Analytics Based on Computational Intelligent Algorithms with the Potential to Reduce Energy Consumption by Chiroma, H., Abdullahi, U.A., Hashem, I.A.T., Saadi, Y., Al-Dabbagh, R.D., Ahmad, M.M., Dada, G.E., Danjuma, S., Maitama, J.Z., Abubakar, A., Abdulhamid, S.�M.

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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.

“…In the agent-based approach to middleware, the agent’s property such as autonomous, mobile and intelligent are suitable as e-assistance tool for big data management. …”
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Investigating the Application of Artificial Intelligence for Earthquake Prediction in Terengganu by Suzlyana Marhain binti Masrizan

Web intelligence: A fuzzy knowledge-based framework for the enhancement of querying and accessing web data by Jaafar, J., Danyaro, K.U., Liew, M.S.

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Development and Integration of Metocean Data Interoperability for Intelligent Operations and Automation Using Machine Learning: A Review by Danyaro, K.U., Hussain, H.H., Abdullahi, M., Liew, M.S., Shawn, L.E., Abubakar, M.Y.

“…A new model integrated with the existing Metocean data system using ML algorithms to monitor and interoperate with maximum performance is proposed. …”
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Predicting longitudinal dispersion coefficient using ensemble models and optimized multi-layer perceptron models by Gholami M., Ghanbari-Adivi E., Ehteram M., Singh V.P., Najah Ahmed A., Mosavi A., El-Shafie A.

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Development of intelligent hybrid learning system using clustering and knowledge-based neural networks for economic forecasting : First phase by Che Mat @ Mohd Shukor, Zamzarina, Md Sap, Mohd Noor

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Development and Integration of Metocean Data Interoperability for Intelligent Operations and Automation Using Machine Learning: A Review by Danyaro, K.U., Hussain, H.H., Abdullahi, M., Liew, M.S., Shawn, L.E., Abubakar, M.Y.

“…A new model integrated with the existing Metocean data system using ML algorithms to monitor and interoperate with maximum performance is proposed. …”
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GA optimization-based BRB AI reasoning algorithm for determining the factors affecting customer churn for operators by Kun, Liu, Alli, Hassan, Abd Rahman, Khairul Aidil Azlin

“…In the era of big data, numerous predictive models are based on more redundant features, which increases the complexity of the algorithms and the difficulty of analyzing customer churn. …”
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Towards paddy rice smart farming: a review on big data, machine learning, and rice production tasks by Rayner Alfred, Joe Henry Obit, Christie Chin Pei Yee, Haviluddin Haviluddin, Yuto Lim

“…The quality of data collected from sensors greatly influences the performance of the modelling processes using ML algorithms. …”
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A new mobile malware classification for SMS exploitation by Zaizi N.J.M., Khailani A., Madihah Mohd Saudi

Mortality Trends and Its Impact on the Pension Liabilities by Rose Irnawaty Ibrahim

Investigating the application of artificial intelligence for earthquake prediction in Terengganu by Marhain S., Ahmed A.N., Murti M.A., Kumar P., El-Shafie A.

Hyperparameter tuned deep learning enabled intrusion detection on internet of everything environment by Ahmed Hamza, Manar, Hassan Abdalla Hashim, Aisha, G. Mohamed, Heba, S. Alotaibi, Saud, Mahgoub, Hany, S. Mehanna, Amal, Motwakel, Abdelwahed

“…On the other hand, the massive increase in data generation from IoE applications enables the transmission of big data, from contextaware machines, into useful data. …”
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Digitisation and Artificial Intelligence in the Islamic Finance Industry: Industry Innovation and Shariah Compliance Automation by Zurina Shafii, Kasumalinda Alwi, Supiah Salleh

Applications of IoT and Artificial Intelligence in Water Quality Monitoring and Prediction: A Review by Mustafa H.M., Mustapha A., Hayder G., Salisu A.

A theoretical framework for big data analytics based on computational intelligent algorithms with the potential to reduce energy consumption by Haruna, Chiroma, Abdullahi, Usman Ali, Targio Hashem, Ibrahim Abaker, Saadi, Younes, Al-Dabbagh, Rawaa Dawoud, Ahmad, Muhammad Murtala, Emmanuel Dada, Gbenga, Danjuma, Sani, Maitama, Jaafar Zubairu, Abubakar, Adamu, Abdulhamid, Shafi’i Muhammad

“…The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. …”
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A review of the inter-correlation of climate change, air pollution and urban sustainability using novel machine learning algorithms and spatial information science by Balogun, A.-L., Tella, A., Baloo, L., Adebisi, N.

“…The study also revealed that machine learning algorithms such as random forest, gradient boosting machine, and classification and regression trees (CART) accurately predict air pollution hazard when integrated with spatial models. …”
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