Predictive modeling for the adsorptive and photocatalytic removal of phenolic contaminants from water using artificial neural networks by Shahzar Hafeez, Ayesha Ishaq, Azeem Intisar, Tariq Mahmood, Muhammad Imran Din, Ejaz Ahmed, Muhammad Rizwan Tariq, Muhammad Amin Abid

“…Artificial Intelligence (AI) is employed for the interpretation of treatment-based processes due to powerful learning, simplicity, high estimation accuracy, effectiveness, and improvement of process efficiency where artificial neural networks (ANNs) are most frequently employed for predicting and analyzing the efficiency of processes applied for the mitigation of these phenolic contaminants from water. …”
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Discrete Phase Shift IRS-Assisted Energy Harvesting in Cognitive Radio Networks With Spectrum Sensing by Lilian Chiru Kawala, Guoquan Li, Mihertie Habtamu Demeke, Junzhou Xiong, Hao Xiong, Hang Hu

“…Simulation results demonstrate the superior performance of the proposed framework and the novel resource allocation algorithm based on alternating optimization. These results highlight the transformative potential of IRS with discrete phase shifts in enhancing EH-CRN efficiency, particularly in improving energy harvesting and SU throughput under practical constraints.…”
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5G-oriented information sharing mechanism within D2D clusters by Shaomin WANG, Bin ZHOU

“…Device-to-Device（D2D）communication is an important technology in 5G network.It helps to improve the transmission efficiency of data dissemination services.However,due to the extra signaling overhead caused by D2D communications,currently most of enhanced-multicast solutions cannot solve the contradiction between high-efficient data transmission and low-efficient signaling procedure,so as to reduce the overall performance gain.An intra-cluster D2D information sharing algorithm based on matrix analysis which includes centralized and distributed modes was proposed.The proposed algorithm could significantly reduce D2D retransmission times in clusters by adaptively selecting the optimal transmitters and data packets for D2D multicast retransmission,achieving the aim of reducing signaling overhead and transmission delay.…”
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Advanced artificial intelligence with federated learning framework for privacy-preserving cyberthreat detection in IoT-assisted sustainable smart cities by Mahmoud Ragab, Ehab Bahaudien Ashary, Bandar M. Alghamdi, Rania Aboalela, Naif Alsaadi, Louai A. Maghrabi, Khalid H. Allehaibi

“…Eventually, the walrus optimization algorithm (WOA) is used for hyperparameter tuning to improve the parameters of the SSAE approach and achieve optimal performance. …”
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Optimising the Selection of Input Variables to Increase the Predicting Accuracy of Shear Strength for Deep Beams by Mohammed Majeed Hameed, Faidhalrahman Khaleel, Mohamed Khalid AlOmar, Siti Fatin Mohd Razali, Mohammed Abdulhakim AlSaadi

“…The study found that all applied models were significantly improved by the presence of the GAITH algorithm, except for the MLR model. …”
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Performance Evaluation of Intrusion Detection System using Selected Features and Machine Learning Classifiers by Raja Azlina Raja Mahmood, AmirHossien Abdi, Masnida Hussin

“…These evolutionary-based algorithms are known to be effective in solving optimization problems.  …”
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A Short-Term Load Forecasting Method Considering Multiple Factors Based on VAR and CEEMDAN-CNN-BILSTM by Bao Wang, Li Wang, Yanru Ma, Dengshan Hou, Wenwu Sun, Shenghu Li

“…Finally, the sine–cosine and Cauchy mutation sparrow search algorithm (SCSSA) is used to optimize the parameters of the combinative model to improve the forecasting accuracy. …”
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Smart indoor monitoring for disabled individuals using an ensemble of deep learning models in an IoT environment by Faisal S. Alsubaei, Abdulrahman A. Alshdadi, Mohammed Rizwanullah

“…Initially, the SIMDP-EDLIoT approach uses linear scaling normalization (LSN) to ensure that the input data is scaled appropriately. Besides, the Improved Osprey Optimization Algorithm (IOOA)-based feature selection is employed to classify the most relevant features, enhancing the efficiency of the system by reducing dimensionality. …”
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A Statistical Analysis Based Probabilistic Routing for Resource-Constrained Delay Tolerant Networks by Jixing Xu, Jianbo Li, Shan Jiang, Chenqu Dai, Lei You

“…In this paper, we propose an improved probabilistic routing algorithm that fully takes into account message's time-to-live when predicting the delivery probability. …”
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Deep Reinforcement Learning Assisted UAV Path Planning Relying on Cumulative Reward Mode and Region Segmentation by Zhipeng Wang, Soon Xin Ng, Mohammed EI-Hajjar

“…The proposed region segmentation algorithm and cumulative reward model have been tested in different DRL techniques, where we show that the cumulative reward model can improve the training efficiency of deep neural networks by 30.8% and the region segmentation algorithm enables deep Q-network agent to avoid 99% of local optimal traps and assists deep deterministic policy gradient agent to avoid 92% of local optimal traps.…”
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Machine Learning-Augmented Triage for Sepsis: Real-Time ICU Mortality Prediction Using SHAP-Explained Meta-Ensemble Models by Hülya Yilmaz Başer, Turan Evran, Mehmet Akif Cifci

“…<b>Background/Objectives:</b> Optimization algorithms are acknowledged to be critical in various fields and dynamical systems since they provide facilitation in identifying and retrieving the most possible solutions concerning complex problems besides improving efficiency, cutting down on costs, and boosting performance. …”
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Prediction of Input–Output Characteristic Curves of Hydraulic Cylinders Based on Three-Layer BP Neural Network by Wei Cai, Yirui Zhang, Jianxin Zhang, Shunshun Guo, Rui Guo

“…In the process of model improvement, a nonlinear adaptive decreasing weight mechanism is introduced to improve the optimization accuracy of the algorithm, facilitating the search for optimal solutions. …”
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Enhancing 4G/LTE Network Path Loss Prediction with PSO-GWO Hybrid Approach by Messaoud Garah, Nabil Boukhennoufa

“…Furthermore, a hybrid optimization model, PSO-GWO, is proposed to improve prediction accuracy. …”
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Random Natural Gradient by Ioannis Kolotouros, Petros Wallden

“…Hybrid quantum-classical algorithms appear to be the most promising approach for near-term quantum applications. …”
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Maximizing the biochemical resolving power of fluorescence microscopy. by Alessandro Esposito, Marina Popleteeva, Ashok R Venkitaraman

“…We describe optimized imaging protocols, provide optimization algorithms and describe precision and resolving power in biochemical imaging thanks to the analysis of the general properties of Fisher information in fluorescence detection. …”
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Finding the Shortest Path with Vertex Constraint over Large Graphs by Yajun Yang, Zhongfei Li, Xin Wang, Qinghua Hu

“…In this paper, we first propose a novel exact heuristic algorithm in best-first search way and then give two optimizing techniques to improve efficiency. …”
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A Hybrid Machine Learning Approach for Predicting Power Transformer Failures Using Internet of Things-Based Monitoring and Explainable Artificial Intelligence by Emrah Aslan, Yildirim Ozupak, Feyyaz Alpsalaz, Zakaria M. S. Elbarbary

“…The proposed hybrid model combines the LightGBM algorithm with GridSearch optimization to achieve both high predictive accuracy and computational efficiency. …”
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Externally bonded reinforcement side extended (EBRSE) technique to postpone debonding of FRP laminates in strengthened concrete elements by Mehdi Aghabagloo, Laura Carreras, Cristina Barris, Alba Codina, Marta Baena

“…Additionally, a numerical approach was applied, combining the finite difference method with a metaheuristic optimization algorithm, to derive the bond-slip law governing the constitutive behavior of both systems. …”
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Joint classification and regression with deep multi task learning model using conventional based patch extraction for brain disease diagnosis by Padmapriya K., Ezhumalai Periyathambi

“…Through cooperative learning of several tasks, the model might make greater use of shared information and improve overall performance. For pre-processing system uses an edge detector, which is canny edge detector. …”
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Mixed Gas Detection and Temperature Compensation Based on Photoacoustic Spectroscopy by Sun Chao, Hu Runze, Liu Niansong, Ding Jianjun

“…It determines the weight ratio of each algorithm through experiments to improve the accuracy of gas category discrimination. …”
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