Enhancing the prediction of groundwater quality index in semi-arid regions using a novel ANN-based hybrid arctic puffin-hippopotamus optimization model by Moustafa Gamal Snousy, Hussein M. Elshafie, Ashraf R. Abouelmagd, Najmaldin Ezaldin Hassan, Mahmoud E. Abd-Elmaboud, Ali Akbar Mohammadi, Ashraf M.T. Elewa, E. EL-Sayed, Ahmed M. Saqr

“…Study focus: This study presents a novel hybrid arctic puffin–hippopotamus optimization (HPHO) algorithm combined with an artificial neural network (ANN) to improve irrigation water quality index (IWQI) predictions in semi-arid areas. …”
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An Optimal Sizing Methodology for a Wind/PV Hybrid Energy Production System for Agricultural Irrigation in Skikda, Algeria by Nadhir Abderrahmane, Allaoua Brahmia, Adlen Kerboua, Ridha Kelaiaia

“…The optimization algorithm used was tailored to the formulated problem, ensuring reliable and applicable results. …”
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Scientific planning of dynamic crops in complex agricultural landscapes based on adaptive optimization hybrid SA-GA method by Changlong Li, Zengye Su, Yudan Nie, Zhiyi Ye, Jinyi Li, Jing Wang, Zicong Yang, Xuxin Li, Weijian Zeng, Yanjian Chen

“…The H-SAGA component optimises planting strategies by synergistically combining global exploration (SA) and local refinement (GA) capabilities, while the neural network dynamically adjusts revenue forecasts based on climatic and market data, significantly improving the model’s responsiveness and adaptability. …”
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Modular Coordination of Vehicle Routing and Bin Packing Problems in Last Mile Logistics by Nikica Perić, Anđelko Kolak, Vinko Lešić

“…<i>Background</i>: Logistics and transport, core of many business processes, are continuously optimized to improve efficiency and market competitiveness. …”
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Tackling the Optimal Phasor Measurement Unit Placement and Attack Detection Problems in Smart Grids by Incorporating Machine Learning by Ramzi Al-Sharawi, Abdelfatah Ali, Mostafa Shaaban, Nasser Qaddoumi, Mohamed S. Abdalzaher

“…Thus, this paper proposes a novel approach by formulating this issue as a tri-objective functions optimization problem. The proposed approach optimizes PMU allocation to maximize topological observability and minimize system cost while improving the FDIA detection performance using machine learning. …”
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Hybrid Machine Learning Model for Predicting Shear Strength of Rock Joints by Daxing Lei, Yaoping Zhang, Zhigang Lu, Hang Lin, Yifan Chen

“…To address these challenges, this study proposes a hybrid ML model that integrates a multilayer perceptron (MLP) with the slime mold algorithm (SMA), termed the SMA-MLP model. While MLP exhibits strong nonlinear mapping capability, SMA enhances its training process through global optimization and parameter tuning, thereby improving predictive accuracy and robustness. …”
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Neural network inspired efficient scalable task scheduling for cloud infrastructure by Punit Gupta, Arnaav Anand, Pratyush Agarwal, Gavin McArdle

“…In this work, we aim to use the Harmony Search Algorithm and neural networks to create a fault aware system for optimal usage of cloud resources. …”
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Hybrid GOA and PSO optimization for load frequency control in renewable multi source dual area power systems by Muhammad Zubair Yameen, Abdul Khalique Junejo, Zhigang Lu, Rizwan Aziz Siddiqui, Fayez F. M. El-Sousy, Ibtisam Naveed

“…To address these challenges, this paper proposes a novel Proportional-Integral-Derivative (PID) controller optimized using a hybrid Grasshopper Optimization Algorithm-Particle Swarm Optimization (GOA-PSO) approach. …”
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A comparative study of different kinematic wake models within metaheuristics for efficient wind farm layout optimization by Antonio J. Romero-Barrera, David Casillas-Pérez, Laura Cornejo-Bueno, Jorge Pérez-Aracil, Alvaro Paricio-Garcia, Miguel A. Lopez-Carmona, Juan Blanco-Sancho, Sujan Ghimire, Ravinesh C. Deo, Antonio J. Caamaño, Sancho Salcedo-Sanz

“…Results show 10-15% efficiency improvements compared to random population initializations, with larger terrains favoring ensemble-based optimization, while denser layouts benefit from evolutionary approaches. …”
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Unboxing Tree ensembles for interpretability: A hierarchical visualization tool and a multivariate optimal re-built tree by Giulia Di Teodoro, Marta Monaci, Laura Palagi

“…The interpretability of models has become a crucial issue in Machine Learning because of algorithmic decisions' growing impact on real-world applications. …”
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Life cycle assessment and multicriteria decision making analysis of additive manufacturing processes towards optimal performance and sustainability by Jayant M. Raut, Prashant B. Pande, Kamlesh V. Madurwar, Rajesh M. Bhagat, Satyajit S. Uparkar, Nilesh Shelke, Haytham F. Isleem, Arpita, Vikrant S. Vairagade

“…For its part, PSO optimizes design and manufacturing parameters for the materials, raising their efficiency by 10–15%, while the energy consumption goes down by 8–12%. …”
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Improving cancer detection through computer-aided diagnosis: A comprehensive analysis of nonlinear and texture features in breast thermograms. by Hamed Khodadadi, Shima Nazem

“…The effectiveness of the proposed approach is enhanced by integrating texture and complexity features. Besides, to optimize feature selection and reduce redundancy, a metaheuristic optimization technique called Non-Dominated Sorting Genetic Algorithm (NSGA III) is applied. …”
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Optimization design of liquid crystal-based reconfigurable intelligent surface-assisted indoor visible light communication systems by Lisu YU, Xinxin LÜ, Run ZHONG, Mingli ZHANG, Zhenghai WANG, Yuhao WANG

“…A low-complexity algorithm using fractional programming and step-by-step optimization is recommended for managing perfect channel state information. …”
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A dimension reduction assisted credit scoring method for big data with categorical features by Tatjana Miljkovic, Pei Wang

“…The evidence suggests that even small improvements in the accuracy of existing credit-scoring models may optimize profits while effectively managing risk exposure. …”
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Hybrid-driven modeling using a BiLSTM–AdaBoost algorithm for diameter prediction in the constant diameter stage of Czochralski silicon single crystals by Yu-Yu Liu, Ding Liu, Shi-Hai Wu, Yi-Ming Jing

“…Subsequently, the prediction results of the BiLSTM network are weighted and fused by the AdaBoost algorithm to obtain the final time series prediction output, and the prediction performance is further enhanced by iterative optimization. …”
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Improved deep learning model for accurate energy demand prediction and conservation in electric vehicles integrated with cognitive radio networks by V. Niranjani, Anandakumar Haldorai

“…To overcome this issue, this paper proposed a model of Empirical Mode Decomposition with CNN and optimized with Seagull Optimization Algorithm (EMD-CNN-SOA). …”
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E-Commerce Logistics Software Package Tracking and Route Planning and Optimization System of Embedded Technology Based on the Intelligent Era by Dan Zhang, Zhiyang Jia

“…To sum up, this algorithm could effectively optimize the distribution route of logistics packages and improve the efficiency of package transportation.…”
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Optimized Quality of Service for Real-Time Wireless Sensor Networks Using a Partitioning Multipath Routing Approach by Mohammed Zaki Hasan, Tat-Chee Wan

“…The proposed approach significantly improves the network lifetime, while reducing energy consumption and decreasing average end-to-end delays within the sensor network via optimised resource sharing in intermediate nodes compared with existing routing algorithms.…”
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Co‐Creation in Automated Public Space Lighting Design: Enhancing Safety and Reducing Light Pollution by Jan Cudzik, Michał Nessel, Victor Moczarski

“…The article presents an algorithm that iteratively determines the optimal number and placement of lamps based on expected lighting levels. …”
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A Lightweight, Intelligent Autonomous Exploration System for Indoor Robots Using Improved Random Walk With Back-Off Strategies by Blesson Mathews Luke, S. Abraham Sampson

“…This study presents the Intelligent Exploration (IE) algorithm, an innovative method that integrates an improved random walk technique, real-time LiDAR-based obstacle avoidance, and a strategic back-off mechanism to optimize exploration efficiency. …”
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