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Distributed learning based energy-efficient operations in small cell networks by Mughees, Amna

“…Simulation results demonstrate improved performance in power consumption, load, sum rate, utility, learning rate, convergence, and energy efficiency for small base stations (SBSs) and user equipment (UEs) compared to four benchmarked algorithms, including WMMSE, game theory, Q-learning, and DRL. …”
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Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

“…To enhance the selection of most highly ranking features, irrelevant features are ‘pruned’ based on determined boundary threshold. In order to estimate the quality of ‘pruned’ features, self-adaptive DE algorithm is proposed. …”
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Chiller energy prediction in commercial building : A metaheuristic-enhanced deep learning approach by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

“…This paper introduces an innovative methodology that integrates deep learning (DL), specifically Fixed Forward Neural Networks (FFNN), with Teaching-Learning-Based Optimization (TLBO) to enhance the accuracy of chiller energy consumption forecasts. …”
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Comparison Performance of Qualitative Bankruptcy Classification based on Data Mining Algorithms by Nilam Nur Amir, Sjarif, Yee, Fang Lim, NurulHuda, Mohd Firdaus Azmi, Kamalia, Kamardin, Doris Wong, Hooi Ten, Hafiza, Abas, Mubarak-Ali, Al-Fahim

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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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Navigating challenges and opportunities of machine learning in hydrogen catalysis and production processes: Beyond algorithm development by Salehmin M.N.I., Tiong S.K., Mohamed H., Umar D.A., Yu K.L., Ong H.C., Nomanbhay S., Lim S.S.

“…With the projected global surge in hydrogen demand, driven by increasing applications and the imperative for low-emission hydrogen, the integration of machine learning (ML) across the hydrogen energy value chain is a compelling avenue. …”

Machine Learning-Based Analysis of Paddy Crop Conditions by Teo, Xiao Hui, Lim, Shu Ting, Goh, Ching Pang

“…This research will apply three machine learning algorithms which are support vector machine (SVM), logistic regression (LR) and random forest (RF) to predict the paddy conditions based on the physical appearances. …”
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Facilitating English Language teaching through AI- based drama in Palestine by Bsharat, Tahani, Sheikh Ahmad, Ismail

“…Artificial Intelligence (AI) has the potential to significantly reshape the landscape of education through the integration of AI- powered tools, personalized learning algorithms, and virtual and augmented reality. …”
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Recognizing malaysia traffic signs with pre-trained deep convolutional neural networks by How D.N.T., Sahari K.S.M., Hou Y.C., Basubeit O.G.S.

Automatic detection of oil palm tree from UAV images based on the deep learning method by Xinni, Liu, Kamarul Hawari, Ghazali, Fengrong, Han, Izzeldin, I. Mohd

“…Therefore, an effective and efficient method is imperative. This paper proposes a new automatic end-to-end method based on deep learning (DL) for detection and counting oil palm trees from images obtained from unmanned aerial vehicle (UAV) drone. …”
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Heart disease prediction using artificial neural network with ADAM optimization and harmony search algorithm by Alyaa Ghazi Mohammed, Mohd Zakree Ahmad Nazri

“…The ADAM optimizer effectively tackles challenges in continuous parameter optimization by dynamically updating the model's weights and biases, adapting the learning rate for each parameter based on accumulated historical gradient information to achieve more efficient minimization of the loss function during training. …”
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User interface and interactivity design guidelines of algorithm visualization on mobile platform by Supli, Ahmad Affandi

“…Moreover, the evaluation of the effectiveness of the AVOMP prototype from 35 participants through laboratory experiments based on the bloom taxonomy test shows that there is a significant difference between students learning sorting algorithms using the manual approach (Pre-Test) and the AVOMP app (Post-Test). …”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

Advances in remote sensing technology, machine learning and deep learning for marine oil spill detection, prediction and vulnerability assessment by Yekeen, S.T., Balogun, A.-L.

“…On the other hand, deep learning modelsâ�� strong feature extraction and autonomous learning capability enhance their detection accuracy. …”
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Exploring employee working productivity: initial insights from machine learning predictive analytics and visualization by Razali, Mohd Norhisham, Ibrahim, Norizuandi, Hanapi, Rozita, Mohd Zamri, Norfarahzila, Abdul Manaf, Syaifulnizam

“…Future research can explore more advanced machine learning algorithms, incorporate time-series analysis for temporal dependencies, and expand data collection from diverse organizational settings to improve the generalizability of predictive models.…”
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Application of boundary-fitted convolutional neural network to simulate non-Newtonian fluid flow behavior in eccentric annulus by Kumar, A., Ridha, S., Ilyas, S.U., Dzulkarnain, I., Pratama, A.

“…The performance of the algorithm is validated with experimental data available from published studies. …”
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IoT-based Machine Learning Comparative Models of Stream Water Parameters Forecasting for Freshwater Lobster by Bakhit, Abdelmoneim Ahmed, Nur Syahirah, Mohd Sabli, Mohd Faizal, Jamlos, Mohd Aminudin, Jamlos, N. H., Ramli, Muhammad Aqil, Hafizzan Nordin, Alhaj, Nura Abdalrhman, Ali, Ehtesham

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