Optimizing Distribution Grid Performance through Electric Vehicle Integration and Stochastic Modeling in Extreme Weather Conditions by A. Niknami, M. Askari, M. Amirahmadi, M. Babaeinik

“…Monte Carlo simulation is employed to model uncertainties, while a multi-objective optimization algorithm is used to solve the problem. …”
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Deep learning algorithm on H&E whole slide images to characterize TP53 alterations frequency and spatial distribution in breast cancer by Chiara Frascarelli, Konstantinos Venetis, Antonio Marra, Eltjona Mane, Mariia Ivanova, Giulia Cursano, Francesca Maria Porta, Alberto Concardi, Arnaud Gerard Michel Ceol, Annarosa Farina, Carmen Criscitiello, Giuseppe Curigliano, Elena Guerini-Rocco, Nicola Fusco

“…Traditional ancillary methods like immunohistochemistry (IHC) to assess TP53 functionality face pre- and post-analytical challenges. This proof-of-concept study employed a deep learning (DL) algorithm to predict TP53 mutational status from H&E-stained whole slide images (WSIs) of BC tissue. …”
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Improving the efficiency and security of passport control processes at airports by using the R-CNN object detection model by Elhoucine Ouassam, Yassine Dabachine, Nabil Hmina, Belaid Bouikhalene

“… The use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. …”
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Water desalination using waste heat recovery of thermal power plant in tropical climate; optimization by AI by Ehsanolah Assareh, Mohammad Firoozzadeh, Mohammad Zoghi, Ali Zare, Yasaman Ghazi, Ali Shahin-Banna

“…The optimization process is facilitated by artificial neural networks and genetic algorithms, utilizing EES and MATLAB software. …”
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6G virtualized beamforming: a novel framework for optimizing massive MIMO in 6G networks by Ahmed M. Alwakeel

“…Our framework employs a combination of advanced machine learning algorithms and software-defined networking to dynamically allocate beamforming resources, improving adaptability in high-density environments and optimizing signal-to-noise ratios. …”
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A deep neural network approach for optimizing charging behavior for electric vehicle ride-hailing fleet by Kaizhe Chen, Jin Liu, Wenjing Lyu, Tianyuan Wang, Jinxi Wen

“…Therefore, this research develops a Neural Network (NN) trained with the Adaptive Moment Estimation (Adam) algorithm, based on 2.14 million charging events. The goal is to analyze current charging behaviors and evaluate the impact of key variables on costs and emissions, providing data-driven insights for potential improvements, thus addressing a critical research gap. …”
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Optimizing precision farming: enhancing machine learning efficiency with robust regression techniques in high-dimensional data by Nour Hamad Abu Afouna, Majid Khan Majahar Ali

“… Smart precision farming leverages IoT, cloud computing, and big data to optimize agricultural productivity, lower costs, and promote sustainability through digitalization and intelligent methodologies. …”
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Prediction and optimization of hardness in AlSi10Mg alloy produced by laser powder bed fusion using statistical and machine learning approaches by İnayet Burcu Toprak

“…A multidisciplinary approach was adopted to optimize production processes, reduce manufacturing costs, and shorten processing times. …”
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Fuzzy logic-based particle swarm optimization for integrated energy management system considering battery storage degradation by Oladimeji Ibrahim, Mohd Junaidi Abdul Aziz, Razman Ayop, Ahmed Tijjani Dahiru, Wen Yao Low, Mohd Herwan Sulaiman, Temitope Ibrahim Amosa

“…Overall, the FLB-PSO algorithm outperforms traditional PSO in terms of robustness to system dynamics, convergence rate, operational cost reduction, and improved energy efficiency.…”
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Balancing conflicting objectives in pre-salt reservoir development: A robust multi-objective optimization framework by Auref Rostamian, Amir Davari Malekabadi, Marx Vladimir De Souda Miranda, Vinicius Edurado Botechia, Denis José Schiozer

“…Optimizing production strategies for gas and oil fields is a critical challenge in petroleum engineering as it involves balancing multiple and often conflicting objectives, for instance, enhancing production rates, reducing operational costs, and mitigating the environmental effects of cumulative water or gas production. …”
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Priority Load Management for Improving Supply Reliability of Critical Loads in Healthcare Facilities Under Highly Unreliable Grids by Ndukwe Henry Ibiam, Fadi Kahwash, Jubaer Ahmed

“…It was found that the priority-based algorithm improved the reliability served to the most critical loads at the expense of the least critical. …”
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Dynamical Modeling, Analysis, and Control of Information Diffusion over Social Networks: A Deep Learning-Based Recommendation Algorithm in Social Network by Kefei Cheng, Xiaoyong Guo, Xiaotong Cui, Fengchi Shan

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AI-Based Classification Model for Low-Energy Buildings: Promoting Sustainable Economic Development of Smart Cities With Spherical Fuzzy Decision Algorithm by Lin Yang

“…AI-based classification models for low-energy buildings are essential in promoting the economic development of smart cities by optimizing energy use, reducing operational costs, and enhancing overall efficiency. …”
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FLIP: A Novel Feedback Learning-Based Intelligent Plugin Towards Accuracy Enhancement of Chinese OCR by Xinyue Tao, Yueyue Han, Yakai Jin, Yunzhi Wu

“…This study develops FLIP (Feedback Learning-based Intelligent Plugin), a lightweight post-processing plugin designed to improve Chinese OCR accuracy across different systems without external dependencies. …”
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Capacity configuration optimization of electricity heat hydrogen regional integrated energy system considering supply-demand uncertainties. by Tianhe Sun, Runqi Sun, Xiaoyi Qian, Baoshi Wang

“…In view of the dual effects of the uncertainties of energy supply and demand in system configuration on power supply reliability and wind power consumption, a min-max-min two-stage robust optimization configuration model aiming at the minimum sum of system investment and operating cost is established for achieving an optimal capacity configuration of multi-vector technologies involved in it. …”
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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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Transactional configuration of innovative development of business ecosystem by E. V. Popov, A. D. Tikhonova, A. S. Zyrianov

“…As a result, the authors have developed an algorithm that aims to create a pool of stakeholders in the business ecosystem in order to achieve sustainable development within the innovative economy through optimized transaction costs. …”
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Comparative Study on Hyperparameter Tuning for Predicting Concrete Compressive Strength by Jeonghyun Kim, Donwoo Lee

“…This study assesses the impact of hyperparameter optimization algorithms on the performance of machine learning-based concrete compressive strength prediction models. …”
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Enhanced leukemia prediction using hybrid ant colony and ant lion optimization for gene selection and classification by Santhakumar D, Gnanajeyaraman Rajaram, Elankavi R, Viswanath J, Govindharaj I, Raja J

“…Gene selection plays a crucial role in the pre-processing of microarray data, aiming to identify a small set of genes that enhances classification accuracy and reduces costs. Traditional methods, such as Genetic Algorithms (GA) and Maximum Relevance Minimum Redundancy (MRMR), have been widely used, but bio-inspired algorithms like Ant Colony Optimization (ACO) and Ant Lion Optimizer (ALO) have shown promising results. …”
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