FOX-TSA hybrid algorithm: Advancing for superior predictive accuracy in tourism-driven multi-layer perceptron models by Sirwan A. Aula, Tarik A. Rashid

“…Nature-inspired optimization models have received a great deal of interest due to the performance of these algorithms in solving resourceful and authentic problems. …”
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Validation of an AI-Assisted Terrain-Aided Navigation Algorithm Using Real-World Flight Test Instrumentation Data by Ümit Can Bekar, Bilgehan Tanyeri, Ibrahim Enes Uslu, Nuri Arda Gungor, Gokhan Inalhan

“…The proposed TAN integrates a high-performance terrain server, a digital elevation model, and an efficient line-of-sight algorithm to facilitate terrain-aided navigation. The system utilizes an advanced search algorithm in conjunction with two filter designs, including adaptive filters that dynamically optimize navigation precision and operational efficiency. …”
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Energy Scheduling of Hydrogen Hybrid UAV Based on Model Predictive Control and Deep Deterministic Policy Gradient Algorithm by Haitao Li, Chenyu Wang, Shufu Yuan, Hui Zhu, Bo Li, Yuexin Liu, Li Sun

“…The proposed method is designed to optimize energy management in hydrogen-powered UAVs across diverse flight missions. …”
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OPTIMIZATION-BASED APPROACH TO TILING OF FINITE AREAS WITH ARBITRARY SETS OF WANG TILES by Marek Tyburec, Jan Zeman

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Adaptive Policy-Oriented Cybersecurity: A Decentralized Framework Using Message Passing Algorithms for Dynamic Threat Mitigation by Spyridon Evangelatos, Eleni Veroni, Mariza Konidi, Sophia Karagiorgou, Georgia Dede, Anargyros Baklezos, Christos Nikolopoulos, Panagiotis Sarigiannidis, Sotirios K. Goudos

“…More specifically, we extend the traditional Min-Sum algorithm by incorporating dynamic trust weights that influence policy enforcement decisions, allowing more reliable nodes to have a greater impact while mitigating the risks posed by untrusted entities. …”
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Identifying candidate biomarkers for detecting bronchogenic carcinoma stages using metaheuristic algorithms based on information fusion theory by Bagher Khalvati, Kaveh Kavousi, Amir Hosein Keyhanipour, Masoud Arabfard

“…To identify robust biomarkers, we applied eight metaheuristic algorithms for feature selection, combined with four classification methods and two data fusion techniques to optimize performance. …”
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A Computational Sketch-Based Approach Towards Optimal Product Design Solutions by Paschalis Charalampous

“…The proposed approach enables the transformation of simple hand-drawn sketches into digital models suitable for complex computational simulations and design optimization. Using computer vision algorithms, sketches are processed to generate digital design components that serve as inputs for Finite Element Analysis (FEA). …”
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Thermal-Aware Test Schedule and TAM Co-Optimization for Three-Dimensional IC by Chi-Jih Shih, Chih-Yao Hsu, Chun-Yi Kuo, James Li, Jiann-Chyi Rau, Krishnendu Chakrabarty

“…We used both greedy and simulated annealing algorithms to solve this optimization problem. We compare the results of two assumptions: soft-die mode and hard-die mode. …”
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Optimization of High-Performance Computing Job Scheduling Based on Offline Reinforcement Learning by Shihao Li, Wei Dai, Yongyan Chen, Bo Liang

“…In large-scale, distributed high-performance computing systems, the increasing complexity of job scheduling has expanded along with the growth of computational resources and job diversity. While heuristic scheduling strategies with various optimization objectives have shown promising results, their effectiveness is often limited in real-world applications due to the dynamic nature of workloads and system configurations. …”
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Optimizing Natural Image Quality Evaluators for Quality Measurement in CT Scan Denoising by Rudy Gunawan, Yvonne Tran, Jinchuan Zheng, Hung Nguyen, Rifai Chai

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ICSO: A Novel Hybrid Evolutionary Approach with Crisscross and Perturbation Mechanisms for Optimizing Generative Adversarial Network Latent Space by Zhihui Chen, Ting Lan, Zhanchuan Cai, Zonglin Liu, Renzhang Chen

“…This paper proposes a novel improved crisscross optimization (ICSO) algorithm, a hybrid evolutionary approach that integrates crisscross optimization and perturbation mechanisms to find the suitable latent vector. …”
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Optimal Low-Carbon Scheduling for Smart Microgrids With Dynamic Thermal Capacity Constraints by Peng Xie, Hongwei Liu, Chun Chen, Mingjun Liu

“…This study aims to integrate electric vehicles, photovoltaic and battery energy storage systems, and distribution network information in a microgrid to achieve decarbonized optimal operation. Under the different operating states of distribution networks, the paper proposes a decarbonized two-stage deeply integrated operational mode for a photovoltaic, battery energy storage system, and electric vehicles integrated microgrid, incorporating the electricity market to optimize overall revenue. …”
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Optimizing Inotropic Infusion With Cluster Specific AI Decision Models and Digital Twins by Vidya S Nair, G. D. Heshan Niranga, Aryalakshmi C.S, Dipu T. Sathyapalan, Thushara Madathil, Rahul Krishnan Pathinarupothi

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Machine Learning‐Enhanced Optimization for High‐Throughput Precision in Cellular Droplet Bioprinting by Jaemyung Shin, Ryan Kang, Kinam Hyun, Zhangkang Li, Hitendra Kumar, Kangsoo Kim, Simon S. Park, Keekyoung Kim

“…To address these obstacles, machine learning is employed to optimize five critical printing parameters (i.e., bioink viscosity, nozzle size, printing time, printing pressure, and cell concentration), and develop algorithms capable of immediate cellular droplet size prediction. …”
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Optimizing Immunotherapy: The Synergy of Immune Checkpoint Inhibitors with Artificial Intelligence in Melanoma Treatment by Mohammad Saleem, Abigail E. Watson, Aisha Anwaar, Ahmad Omar Jasser, Nabiha Yusuf

“…This study reviews the potential of artificial intelligence (AI) to optimize ICI therapy in melanoma by integrating various diagnostic tools. …”
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Integrating IT and OT for Cybersecurity: A Stochastic Optimization Approach via Attack Graphs by Gonzalo Martinez Medina, Krystel K. Castillo-Villar, Tanveer Hossain Bhuiyan

“…The defense strategies identified by our approach demonstrate that robust security protection can be achieved with optimal resource allocation, providing robust protection while minimizing implementation costs across the most critical vulnerabilities in the manufacturing network.…”
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Differentiable Deep Learning Surrogate Models Applied to the Optimization of the IFMIF-DONES Facility by Galo Gallardo Romero, Guillermo Rodríguez-Llorente, Lucas Magariños Rodríguez, Rodrigo Morant Navascués, Nikita Khvatkin Petrovsky, Rubén Lorenzo Ortega, Roberto Gómez-Espinosa Martín

“…This approach has resulted in models that are able of approximating complex simulations with high accuracy (less than 17% percentage error for the worst case) and significantly reduced inference time (ranging from 2 to 6 orders of magnitude) while being differentiable. The substantial speed-up factors enable the application of online reinforcement learning algorithms, and the differentiable nature of the models allows for seamless integration with differentiable programming techniques, facilitating the solving of inverse problems to find the optimal parameters for a given objective. …”
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OPT-IQA: Automated camera parameters tuning framework with IQA-guided optimization by Jan-Henner Roberg, Vladyslav Mosiichuk, Ricardo Silva, Luís Rosado

“…It also facilitates the seamless integration of supplementary IQA metrics and optimization algorithms to support additional use cases. …”
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Electrical discharge machining: Recent advances and future trends in modeling, optimization, and sustainability by Muhamad Taufik Ulhakim, Sukarman, Khoirudin, Dodi Mulyadi, Hendri Susilo, Rohman, Muji Setiyo

“…Advanced modeling techniques, such as finite element analysis (FEA) and artificial intelligence (AI)-driven simulations, have improved the accuracy of process predictions, enabling real-time adjustments and precise control of machining parameters. Optimization approaches, including machine learning-based algorithms, multi-objective optimization, and hybrid methods, have enhanced key performance indicators, such as material removal rate (MRR), surface quality, and tool wear, thereby increasing process efficiency and reducing machining time. …”
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A Computable Phenotype Algorithm for Postvaccination Myocarditis/Pericarditis Detection Using Real-World Data: Validation Study by Matthew Deady, Raymond Duncan, Matthew Sonesen, Renier Estiandan, Kelly Stimpert, Sylvia Cho, Jeffrey Beers, Brian Goodness, Lance Daniel Jones, Richard Forshee, Steven A Anderson, Hussein Ezzeldin

“…ResultsThe algorithm required 200-250 hours to implement and optimize. …”
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