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

“…By using Stochastic Forest, an improvement in decision accuracy can be attained to the extent of 15–20%, together with a cut in costs of about 10%. …”
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Optimizing drone-based pollination method by using efficient target detection and path planning for complex durian orchards by Ruipeng Tang, Jianxun Tang, Mohamad Sofian Abu Talip, Narendra Kumar Aridas, Binghong Guan

“…For path planning, we develop an Enhanced TSP (EN-TSP) algorithm based on a branch and bound strategy with least-cost optimization. …”
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Accurate Localization Method Combining Optimized Hybrid Neural Networks for Geomagnetic Localization with Multi-Feature Dead Reckoning by Suqing Yan, Baihui Luo, Xiyan Sun, Jianming Xiao, Yuanfa Ji, Kamarul Hawari bin Ghazali

“…To address these issues, we propose a fusion localization algorithm based on particle swarm optimization. First, we construct a five-dimensional hybrid LSTM (5DHLSTM) neural network model, and the 5DHLSTM network structure parameters are optimized via particle swarm optimization (PSO) to achieve geomagnetic localization. …”
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Artificial Intelligence-Driven Approach to Optimizing Boiler Power Generation Efficiency: The Advanced Boiler Combustion Control Model by Kyu-Jeong Lee, So-Won Choi, Eul-Bum Lee

“…Consequently, achieving stable combustion control of these gases is critical for improving boiler efficiency. This study developed the advanced boiler combustion control model (ABCCM) by combining the random forest (RF) and classification and regression tree (CART) algorithms to optimize the combustion of steam power boilers using steel by-product gases. …”
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Utilizing Enhanced Particle Swarm Optimization for Feature Selection in Gender-Emotion Detection From English Speech Signals by Ammar Amjad, Li-Chia Tai, Hsien-Tsung Chang

“…The gender-specific DGA-EBPSO algorithm incorporates a hybrid mutation strategy to improve feature selection efficiency and considers gender-based variations in emotional expression. …”
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Optimizing guest experience in smart hospitality: Integrated fuzzy-AHP and machine learning for centralized hotel operations with IoT by Sinan Andan Diwan

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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

“…Existing research primarily addresses cybersecurity by focusing on the optimal placement of phasor measurement units (PMUs) to ensure topological observability and minimize system costs, followed by developing AI-based attack detection algorithms. …”
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Intelligent Optimized Combined Model Based on GARCH and SVM for Forecasting Electricity Price of New South Wales, Australia by Yi Yang, Yao Dong, Yanhua Chen, Caihong Li

“…In this paper, we propose an optimized combined forecasting model by ant colony optimization algorithm (ACO) based on the generalized autoregressive conditional heteroskedasticity (GARCH) model and support vector machine (SVM) to improve the forecasting accuracy. …”
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An efficient enhanced stacked auto encoder assisted optimized deep neural network for forecasting Dry Eye Disease by Steffi Rajan, Suresh Ponnan

“…The approach described here is novel because it merges chaotic maps into FS, employs SLSTM-STSA for improved classification accuracy (CA), and optimizes with the adaptive quantum rotation of the Enhanced Quantum Bacterial Foraging Optimisation Algorithm (EQBFOA). …”
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An effectiveness of deep learning with fox optimizer-based feature selection model for securing cyberattack detection in IoT environments by Mimouna Abdullah Alkhonaini

“…Furthermore, the FOFSDL-SCD model utilizes the Fox optimizer algorithm (FOA) method for the feature selection process to select the most significant features from the dataset. …”
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Optimization of Laser-Induced Hybrid Hardening Process Based on Response Surface Methodology and WOA-BP Neural Network by Qunli Zhang, Jianan Ling, Zhijun Chen, Guolong Wu, Zexin Yu, Yangfan Wang, Jun Zhou, Jianhua Yao

“…This study uses Box–Behnken design (BBD) experiments to analyze key process parameters and develops response surface methodology (RSM) and whale-optimization-algorithm-optimized back-propagation neural network (WOA-BPNN) models for prediction and optimization. …”
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Parametric Optimization of Train Brake Pad Using Reverse Engineering with Digital Photogrammetry 3D Modeling Method by P Paryanto, Muhammad Faizin, R Rusnaldy

“…This was followed by processing 2D images using Agisoft Metashape 2.2.1 software and Artificial Intelligence (AI) algorithms to create a precise 3D model. Subsequently, assessment was performed using feasibility in terms of cost, time, and accuracy. …”
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Robust GNSS/INS Tightly Coupled Positioning Using Factor Graph Optimization with P-Spline and Dynamic Prediction by Bokun Ning, Fang Zhao, Haiyong Luo, Dan Luo, Wenhua Shao

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Power Enhancement under Partial Shading Condition Using a Two-Step Optimal PV Array Reconfiguration by Mohamad Hossien Nahidan, Mehdi Niroomand, Behzad Mirzaeian Dehkordi

“…The introduced algorithm searches for all possible connections and finally identifies the most optimal solution. …”
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Traction Drive Control System for Railway Electric Rolling Stock Based on the Application of Power Factor as an Optimization Criterion by Goolak S., Gorobchenko O., Holub H., Kulbovskiy I., Petrychenko O.

“…The stated objective has been achieved through the solution of the following tasks: development of an algorithm for applying traction drive power factor as an optimization criterion, taking into account stochastic disturbance effects acting on the traction drive from the traction power supply system and mechanical load; development of a structural scheme for an optimized automatic control system of electric rolling stock traction drives, in which the proposed algorithm is implemented. …”
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Optimal energy management for multi-energy microgrids using hybrid solutions to address renewable energy source uncertainty by M. Siva Ramkumar, Jaganathan Subramani, M. Sivaramkrishnan, Arunkumar Munimathan, Goh Kah Ong Michael, Mohammad Mukhtar Alam

“…In this study, a new hybrid algorithm is used for system modelling and low-cost, optimal management of Micro Grid (MG) networked systems. …”
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Robust techno-economic optimization of energy hubs under uncertainty using active learning with artificial neural networks by Aya M. A. Heikal, Shady H. E. Abdel Aleem, Ragab A. El-Sehiemy, Almoataz Y. Abdelaziz

“…Results demonstrate significant improvements in system reliability, cost efficiency, and flexible operation, validating the effectiveness of ANN-based AL to optimize EHs management and ensure sustainable operation complexities. …”
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Modified invasive weed optimization MPPT approach for PV system interfaced with BLDC motor for water pumping system by S. Nagaraja Rao, B. M. Kiran Kumar, B. M. Manjunatha, A. Suresh Kumar

“…Therefore, the modified invasive weed optimization (MIWO) approach integrated with P&O approach to improve performance under PSC. …”
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Optimized actuator design for flapping-wing robots: A multi-objective approach to mimic natural flapping dynamics by Peiqi Li, Zhiwei Ai, Mufan Zhang

“…The optimization utilized the NSGA-II algorithm. Additionally, a virtual prototype with rigid-flexible coupling was created for simulation assessments pre- and post-optimization. …”
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Construction of Clinical Predictive Models for Heart Failure Detection Using Six Different Machine Learning Algorithms: Identification of Key Clinical Prognostic Features by Qu FZ, Ding J, An XF, Peng R, He N, Liu S, Jiang X

“…Following the elimination of features with significant missing values, the remaining features were utilized to construct predictive models employing six machine learning algorithms. The optimal model was selected based on various performance metrics, including the area under the curve (AUC), accuracy, precision, recall, and F1 score. …”
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