Path planning of unmanned ships based on A* and dynamic window approach by FU Long, SHEN Zhen, TAO Hao, HAN Yunjun, DONG Xisong, XIONG Gang

“…To address the challenge of balancing global optimization, efficiency, and safety in path planning, a method that integrates global search and local optimization was proposed, based on the A* algorithm and the dynamic window approach (DWA). The A* algorithm computed the global shortest path in a static environment, while the improved DWA optimized local path obstacle avoidance between path nodes. …”
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PEDAGOGICAL TECHNOLOGY AIMED AT STUDENTS’ ADAPTATION TO DISCIPLINE-BASED EDUCATION IN SECONDARY SCHOOLS by Ekaterina M. Cheprakova, Alexander A. Frolov

“…These objectives can be achieved through generation of skills based on the algorithmic of the concepts’ definitions mastering. …”
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BOOTSTRAPPING METHODS FOR CONSTRUCTING CONFIDENCE INTERVALS FOR THE ESTIMATION OF MODEL PARAMETERS OF THE ZONAL DISINTEGRATION OF ROCKS AROUND UNDERGROUND EXCAVATIONS by Alexsandr S. Losev

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Broadcasting in Stars of Cliques and Path-Connected Cliques by Akash Ambashankar, Hovhannes A. Harutyunyan

“…Determining the broadcast time for a node in an arbitrary network is NP-complete. While polynomial-time algorithms exist for specific network topologies, the problem remains open for many others. …”
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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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Self-consistent gravity model for inferring node mass in flow networks by Daekyung Lee, Wonguk Cho, Heetae Kim, Gunn Kim, Hyeong-Chai Jeong, Beom Jun Kim

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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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Optimized Metamaterials for Design of Enhanced-Performance High Order Mode Dipole-Driven Yagi-Uda Antenna for Millimeter Wave Applications by Bashar A. F. Esmail, Dustin Isleifson, Slawomir Koziel, Anna Pietrenko-Dabrowska

“…The metamaterial array was optimized using the trust-region (TR) algorithm, resulting in a significant gain enhancement, reaching 13.8 dBi at 28 GHz while maintaining the operational bandwidth in terms of impedance matching. …”
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Convolutional neural networks for accurate estimation of canopy cover by F. Puig, R. Gonzalez Perea, A. Daccache, M.A. Soriano, J.A. Rodríguez Díaz

“…Optimizing the neural network was achieved through a Genetic Algorithm (GA), employing an objective function focused on minimizing parameter density while maintaining accuracy. …”
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Optimization of Fusion Method for GF-2 Satellite Remote Sensing Images based on the Classification Effect by Jintong Ren, Wunian Yang, Xin Yang, Xiaoyu Deng, He Zhao, Fang Wang, Lei Wang

“…The results showed that: (1) The best visual effect of GF-2 fusion image was the Pansharp fusion image; The quantitative evaluation results showed that the brightness and information retention of Gram-Schmidt fusion image was the best，while the Pansharp fusion image had the highest correlation with the original multi-spectral image; the NNDiffuse fusion image had the highest clarity, and the PCA fusion image quantitative evaluation effect was the worst; (2) According to the applicability analysis of the fusion images based on different classification algorithms with features information extraction, it could be seen that the NNDiffuse fusion method was used for the fusion of GF-2 image data, and the classification of the fusion images was more suitable by using KNN or Random Trees classification algorithm.…”
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Artificial Intelligence Methods Applied to Catalytic Cracking Processes by Fan Yang, Mao Xu, Wenqiang Lei, Jiancheng Lv

“…AI methods, including data-driven and knowledge-driven algorithms, are widely used in the abnormal condition warning. …”
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Bayesian Network-Based Landslide Susceptibility Safe Route Assessment in the Face of Uncertain Knowledge and Various Information by Xinyu Gao, Bo Wang, Wen Dai, Yuanmin Liu

“…In this study, we propose an integrated framework that combines a Bayesian network (BN)-based landslide susceptibility map (LSM) with an improved A* algorithm for safe and efficient route planning. The BN model effectively integrates multi-source data and uncertainty knowledge to generate an accurate LSM, while the improved A* algorithm combines safety and efficiency considerations to optimize routes. …”
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Runtime–Coherence Tradeoffs for Hybrid Satisfiability Solvers by Vahideh Eshaghian, Soren Wilkening, Johan Aberg, David Gross

“…Many search-based quantum algorithms that achieve a theoretical speedup are not practically relevant since they require extraordinarily long coherence times, or lack the parallelizability of their classical counterparts. …”
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A two-stage robust optimization for EV user-friendly VPP participation in ancillary service markets by Yu Wang, Xiangrui Tong, Yiheng Xie, Bing Chen, Ning Tong, Xiaomei Wu

“…A power allocation strategy was implemented based on a consensus algorithm that takes into account the satisfaction level of EV users participating in ancillary services and the battery degradation cost. …”
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Research on Detection and Counting Method of Green Walnut Based on YOLOv8n-RBP by Bangbang Chen, Keke Tan, Kun Li, Baojian Ma, Xiangdong Liu

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‌Rockburst intensity grading prediction based on the LOF-ENN-KNN model‌ by Haoran Ge, Jiyong Zhang, Congbo Ma, Kai Hui, Yicong Li, Ziniu Wu

“…Through the comparison and exploration of different sampling methods and different combinations of LOF algorithm, single resampling technology (SMOTE, ADASYN) or simple technology superposition (LOF-SMOTE, LOF-ADASYN) is easy to introduce over-fitting or negative coupling effect, while LOF-ENN-KNN significantly improves the robustness and generalization ability of the model through modular design. …”
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Counting touching wheat grains in images based on elliptical approximation by D. R. Avzalov, E. G. Komyshev, D. A. Afonnikov

“…The number of grains of a cereal plant characterizes its yield, while grain size and shape are closely related to its weight. …”
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Optimising Warehouse Order Picking: Real Case Application in the Shoe Manufacturing Industry by Rodrigo Furlan de Assis, William de Paula Ferreira, Alexandre Frias Faria, Luis Antonio Santa-Eulalia, Mustapha Ouhimmou, Ali Gharbi

“…To address this challenge, we present the Genetic Route Optimisation algorithm for optimising order-picking routes. Our methodology involved testing the proposed algorithm using real-world data derived from the company’s Warehouse Management System. …”
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Novel distance-fitness learning scheme for ameliorating metaheuristic optimization by Emre Çelik, Essam H. Houssein, Mahmoud Abdel-Salam, Diego Oliva, Ghanshyam G. Tejani, Nihat Öztürk, Sunil Kumar Sharma, Mohammed Baljon

“…An important portion of metaheuristic algorithms is guided by the fittest solution obtained so far. …”
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Optimizing dance motion reconstruction using a two-dimensional matrix approach with hybrid genetic and fuzzy logic differential evolution by Lin Wang, Yutong Liu, Yucong Geng, Mohammad Khishe

“…We develop the Two-Dimensional Matrix-Calculation (TDMC) model, combined with the Hybrid Genetic Algorithm with Fuzzy Logic Differential Evolution (HGA-FLDE), which aims to optimize the reconstruction of complex dance movements by leveraging Riemannian geometry and adaptive optimization for biomechanical nonlinear motion patterns and missing joint data. …”
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