Landslides in the Himalayas: The Role of Conditioning Factors and Their Resolution in Susceptibility Mapping by Lalit Pathak, Badri Baral, Kamana Joshi, Dipak Raj Basnet, Danilo Godone

“…Sixteen factors, encompassing topography, hydrology, geology, and anthropogenic activities, were analyzed alongside a landslide inventory of 159 occurrences compiled from satellite imagery, the literature, and field surveys. A genetic algorithm (GA) was employed to determine the optimal set of conditioning factors, while Maximum Entropy (Maxent) modeling produced landslide susceptibility maps (LSM) at spatial resolutions ranging between 12.5 and 200 m. …”
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Life cycle low-carbon capacity optimization planning of integrated energy systems in manufacturing enterprise parks by Tianyi Ma, Jianxiong Qiu, Hu Wang, Lijun Zhang, Xiaojie Lin, Yanling Wu, Hongfei Zhao, Wei Zhong, Yanxin Wang, Zitao Yu, Changhe Zhou, Jian Cheng, Liuliu Du-Ikonen, Xiaolei Yuan

“…The optimization is solved using Non-dominated Sorting Genetic Algorithm II (NSGA-II) combined with the entropy weight method and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). …”
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Deceptive Cyber-Resilience in PV Grids: Digital Twin-Assisted Optimization Against Cyber-Physical Attacks by Bo Li, Xin Jin, Tingjie Ba, Tingzhe Pan, En Wang, Zhiming Gu

“…A non-dominated sorting genetic algorithm (NSGA-III) is employed to achieve Pareto-optimal solutions, ensuring high system resilience while minimizing computational burdens. …”
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Optimization of Remote Backup Protection Coordination Logic Based on Dynamic Identification of Faulty Components in Transmission Grids by LIN Xiangning, JI Jihao, DING Yifan, LI Zhengtian, WENG Hanli

“…For symmetrical faults， the traveling wave ranging error is less than 100 m， and the location time is reduced by 90% compared with traditional methods. After optimization， the remote backup-action delay was reduced from 4-7 intervals to 2 intervals， while the setting coverage increased by 18.4%， effectively avoiding misoperations owing to load intrusion. …”
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Utilizing molecular simulation, ideal adsorbed solution theory and ensemble learning algorithms to investigate adsorption and separation of sulfides on amorphous nanoporous materia... by Xuan Peng, Xingbang Zhang

“…For CH4-H2S mixture, despite aCarbon-Marks-id002 exhibiting the highest selectivity (approximately 80), the H2S adsorption was low (around 1 mmol/g), while Kerogen-Coasne-id013 demonstrated a high H2S adsorption of 12 mmol/g with a selectivity of 20. …”
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A Robust Gaze Estimation Approach via Exploring Relevant Electrooculogram Features and Optimal Electrodes Placements by Zheng Zeng, Linkai Tao, Hangyu Zhu, Yunfeng Zhu, Long Meng, Jiahao Fan, Chen Chen, Wei Chen

“…The MAE and RMSE can be improved to 2.80° and 3.74° ultimately, while only using 10 features extracted from 2 channels. …”
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MbGWO-SFS: Modified Binary Grey Wolf Optimizer Based on Stochastic Fractal Search for Feature Selection by El-Sayed M. El-Kenawy, Marwa Metwally Eid, Mohamed Saber, Abdelhameed Ibrahim

“…The results, compared to binary versions of the-state-of-the-art optimization techniques such as the original GWO, SFS, Particle Swarm Optimization (PSO), hybrid of PSO and GWO, Satin Bowerbird Optimizer (SBO), Whale Optimization Algorithm (WOA), Multiverse Optimization (MVO), Firefly Algorithm (FA), and Genetic Algorithm (GA), show the superiority of the proposed algorithm. …”
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Enhancing Hybrid Flow Shop Scheduling Problem with a Hybrid Metaheuristic and Machine Learning Approach for Dynamic Parameter Tuning by Ahmed Abdulmunem Hussein

“…Specifically, we propose a hybrid algorithm by combining Ant Colony Optimization (ACO) and Iterated Local Search (ILS) to form ACOILS. …”
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Hybrid Automata-Based Control Framework for Real-Time Optimization in Space-Based Solar Power Transmission by Patil Ankita, Ranjan Mritunjay, Deore Kalyani, Sonje Pranjal, Patil Kiran, Patil Rutuja

“…SBSP systems suffer from some serious challenges, such as beam angle error deviations, power transmission efficiency reduction, atmospheric disturbance, and space debris impact. While usual machine learning algorithms may predict the production of energy, they cannot respond sufficiently in real time to alter according to dynamic environmental conditions. …”
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A Method for Improving the Monitoring Quality and Network Lifetime of Hybrid Self-Powered Wireless Sensor Networks by Peng Wang, Yonghua Xiong

“…Finally, a method based on an improved nutcracker optimizer algorithm is proposed to solve the optimal working sequence of nodes, schedule the “sleep or work” state of nodes, and extend the network lifetime. …”
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A lightweight and optimized deep learning model for detecting banana bunches and stalks in autonomous harvesting vehicles by Duc Tai Nguyen, Phuoc Bao Long Do, Doan Dang Khoa Nguyen, Wei-Chih Lin

“…Notably, the proposed model outperforms the previous detection models, offering high accuracy while optimizing computational efficiency. These advancements make the proposed model highly suitable for deployment on embedded systems in agricultural robots.…”
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Application of Metaheuristics for Optimizing Predictive Models in iHealth: A Case Study on Hypotension Prediction in Dialysis Patients by Felipe Cisternas-Caneo, María Santamera-Lastras, José Barrera-Garcia, Broderick Crawford, Ricardo Soto, Cristóbal Brante-Aguilera, Alberto Garcés-Jiménez, Diego Rodriguez-Puyol, José Manuel Gómez-Pulido

“…Dialysis session data from 758 patients collected between January 2016 and October 2019 were analyzed. Particle Swarm Optimization, Grey Wolf Optimizer, Pendulum Search Algorithm, and Whale Optimization Algorithm were employed to reduce the feature space, removing approximately 45% of clinical and analytical variables while maintaining high recall for the minority class of patients experiencing hypotension. …”
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Optimizing cervical cancer classification using transfer learning with deep gaussian processes and support vector machines by Emmanuel Ahishakiye, Fredrick Kanobe

“…These algorithms are (1) an optimized support vector machine (SVM), and (2) a deep Gaussian Process (DGP) model. …”
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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

“…This work demonstrates the potential of hybrid optimization techniques in bioinformatics for better gene selection and cancer diagnosis. • Hybrid ACO-ALO approach combines strengths of both algorithms for better feature selection. • Enhances classifier performance while reducing computational complexity. • Outperforms traditional methods on leukemia prediction datasets.…”
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Optimization of Adaptive Observation Strategies for Multi-AUVs in Complex Marine Environments Using Deep Reinforcement Learning by Jingjing Zhang, Weidong Zhou, Xiong Deng, Shuo Yang, Chunwang Yang, Hongliang Yin

“…Traditional algorithms struggle with the strong coupling between environmental information and observation modeling, making it challenging to derive optimal strategies. …”
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Parametric Optimization and Assessment of Modern Heritage Shading Screen for a Mid-Rise Building in Arid Climate: Modernizing Traditional Designs by Anwar Ahmad, Lindita Bande, Waleed Ahmed, Kheira Tabet Aoul, Mukesh Jha

“…This research explores how parametric design and optimization based on genetic algorithms (GAs) can improve shading structures to reduce solar radiation and lower cooling energy consumption. …”
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Short-term scheduling optimization of battery electric buses in the context of sustainable energy resources under uncertainty by Muhammad Ahmad Iqbal, Ismail I. Almaraj

“…Consequently, the proposed framework effectively balances operational efficiency with resilience against price volatility, supporting reliable scheduling operations while optimizing renewable energy integration and enhancing grid flexibility.…”
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Utility-based optimization of Fujikawa's basket trial design - Pre-specified protocol of a comparison study. by Lukas D Sauer, Alexander Ritz, Meinhard Kieser

“…In a comparison study using simulations and numerical calculations, we are planning to investigate the use of utility functions for quantifying the compromise between power and type-I error inflation and the use of numerical optimization algorithms for optimizing these functions. …”
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Active and Reactive Power Control for Wind Turbines Based DFIG Using LQR Controller with Optimal Gain-Scheduling by Ashraf Radaideh, Mu’men Bodoor, Ayman Al-Quraan

“…The performance of the optimal controller represented by a linear quadratic regulator is further enhanced using the whale optimization algorithm in a multiobjective optimization environment. …”
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Optimizing radiomics for prostate cancer diagnosis: feature selection strategies, machine learning classifiers, and MRI sequences by Eugenia Mylona, Dimitrios I. Zaridis, Charalampos Ν. Kalantzopoulos, Nikolaos S. Tachos, Daniele Regge, Nikolaos Papanikolaou, Manolis Tsiknakis, Kostas Marias, ProCAncer-I Consortium, Dimitrios I. Fotiadis

“…Key Points Radiomics is a growing field that can still be optimized. Feature selection method impacts radiomics models’ performance more than ML algorithms. …”
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