Predicting Trip Duration and Distance in Bike-Sharing Systems Using Dynamic Time Warping by Ahmed Ali, Ahmad Salah, Mahmoud Bekhit, Ahmed Fathalla

“…Accurate prediction of ride duration allows a better estimate of bike availability at stations, while distance predictions assist in maintenance planning based on bike usage patterns. …”
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Damage Identification in Large-Scale Structures Using Time Series Analysis and Improved Sparse Regularization by Huihui Chen, Xiaojing Yuan

“…Compared to the moth-flame optimization (MFO) algorithm and traditional regularization methods, for both noise-free and noise polluted data, the iteration curves illustrate that the proposed method can achieve convergence within about 200 iterations, while the MFO algorithm is always trapped into local optima; meanwhile, the traditional regularization method needs more iterations or even cannot meet the preset tolerance. …”
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Pavement pothole detection system based on deep learning and binocular vision by Tian Guan, Jianyuan Cai, Yu Wang, Wei Yang, Xiaobo Chang, Yi Han

“…Finally, vehicle experiments were conducted to verify the effectiveness of the algorithm in meeting detection requirements while considering long-range perception accuracy. …”
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A novel flexible near-infrared endoscopic device that enables real-time artificial intelligence fluorescence tissue characterization. by Gareth Gallagher, Ra'ed Malallah, Jonathan P Epperlein, Jeffrey Dalli, Niall Hardy, Abhinav Jindal, Pol G MacAonghusa, Ronan A Cahill

“…Jaccard Index comparison of the AI -generated flow regions against manually delineated flow regions resulted in 79% accuracy. While further clinical validation of the AI-NIR polyp classification method is on-going (in the Horizon Europe Awarded CLASSICA project), other use case applications of NIR colonoscopy include simpler perioperative perfusion assessment in patients undergoing colorectal resection and combination with targeted agents in development thus encouraging continuing development and design optimization of this flexible NIR imaging probe to enable clinical and commercial translation.…”
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Research on Anti-Interference Performance of Spiking Neural Network Under Network Connection Damage by Yongqiang Zhang, Haijie Pang, Jinlong Ma, Guilei Ma, Xiaoming Zhang, Menghua Man

“…On the MNIST dataset, the accuracy of the spiking neural network decreased by 3.91% at a sparsity of 30%, while the artificial neural network decreased by 10.13%. …”
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Analytical Designing of Optimum Controller for Linear-Quadratic Functional with the Given Limiting Restrictions by V. I. Timoshpolskii, V. B. Kovalevskii, G. Romadan, P. V. Ilyusenko

“…This methodology may be used in resource saving technologies while soaking metal in the furnace. The paper reveals new methods of optimization that do not have analogues.…”
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Comparison between Logistic Regression and K-Nearest Neighbour Techniques with Application on Thalassemia Patients in Mosul by Mohammed Al jbory, Hutheyfa Taha

“… The experimental results showed that the logistic regression model performed better than the nearest neighbor algorithm with a precision of 96%, recall of 98%, and F1- score of 97% in the thalassemia intermedia category, while it had a precision of 97%, recall of 95%, and F1- score of 96% in the thalassemia major category, indicating that logistic regression performed well in distinguishing between these two categories. it has been shown that logistic regression is more effective than the K-nearest neighbor algorithm in classifying thalassemia patients, especially those with thalassemia major. …”
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Effect of Voltage Dependent Load Model on Placement and Sizing of Distributed Generator in Large Scale Distribution System by Gopisetti Manikanta, Ashish Mani, Hemender Pal Singh, Devendra Kumar Chaturvedi

“…In addition to AQiEA, four other algorithms (Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), Grey Wolf Optimization (GWO), and Ecogeography-based Optimization (EBO) with Classification based on Multiple Association Rules (CMAR)) have also been employed for comparison. …”
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User preference–based QoS-aware service function placement in IoT-Edge cloud by Briytone Mutichiro, Younghan Kim

“…The proposed solutions are evaluated based on different metrics and the obtained results show the gap between the heuristic user preference placement algorithm and the optimal solution to be minimal.…”
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Three-Dimensional Temperature Field Reconstruction Based on Tucker Decomposition and Acoustic Thermometry by Jidong Yan, Liansuo An, Pengbo Yao, Guoqing Shen, Shiping Zhang

“…Our method achieves faster reconstruction speeds (approximately 4 s) and higher accuracy, reducing reconstruction errors by over 10% compared to traditional acoustic thermometry. Additionally, the algorithm demonstrates strong anti-noise capabilities and applicability to temperature fields beyond the a priori conditions, making it a valuable tool for combustion optimization and load adjustment in coal-fired power plants.…”
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Planning and layout of tourism and leisure facilities based on POI big data and machine learning. by Shifeng Wu, Jiangyun Wang, Yinuo Jia, Jintian Yang, Jixiu Li

“…By leveraging machine learning algorithms for facility siting, this study aims to enhance the overall urban layout while mitigating the inherent subjectivity in planning and location decisions, offering valuable insights for the site selection of diverse facilities.…”
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Joint Allocation of Shared Yard Space and Internal Trucks in Sea–Rail Intermodal Container Terminals by Xiaohan Wang, Zhihong Jin, Jia Luo

“…Numerical experiments verify the model and algorithm performance, revealing that the proposed method achieves an optimality gap of only 1.82% compared to CPLEX in small-scale instances while outperforming benchmark algorithms in solution quality. …”
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Simulation analysis of path planning for workpiece clamping robots based on digital twin technology by Xin PAN, Min LIANG, Yanchao YIN, Zhong CHEN

“…Targeting feasible regions through elliptical constraints accelerates convergence toward optimal paths, while techniques such as redundant node elimination and initial path smoothing further improve path quality, resulting in shorter, smoother routes. …”
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A Collaborative Transit Signal Priority Method Considering Gaming among Traffic Participants by Bing Wu, Haishan Wang, Yanli Wang, Ben Zhai, TanXing Xue

“…Different from previous studies, Co-TSP uses game theory to realize collaborative optimization, instead of transforming the problem into a single objective optimization problem by weighting. …”
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Investigating the Machining Behavior of the Additively Manufactured Polymer-Based Composite Using Adaptive Neuro-Fuzzy Learning by Anastasios Tzotzis, Dumitru Nedelcu, Simona-Nicoleta Mazurchevici, Panagiotis Kyratsis

“…Multi-objective optimization using the Non-Dominated Sorting Genetic Algorithm 2 (NSGA-II) algorithm was employed to minimize both <i>Ra</i> and <i>T</i> simultaneously. …”
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Rate of penetration prediction in drilling operations: a comparative study of AI models and meta-heuristic approaches by Fatemeh Mohammadinia, Ali Ranjbar, Fatemeh Ghazi, Seyyed Taha Hosseini

“…To further enhance model performance, metaheuristic optimization strategies such as the Crow Search Algorithm (CSA), Particle Swarm Optimization (PSO), and Genetic Algorithm (GA) are integrated. …”
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Rolling Bearing Fault Diagnosis Based on Adaptive Multiparameter-Adjusting Bistable Stochastic Resonance by Z. H. Lai, S. B. Wang, G. Q. Zhang, C. L. Zhang, J. W. Zhang

“…Furthermore, the influence of algorithm parameters on the optimization results is discussed, and the optimization results of the Langevin system and the Duffing system are compared. …”
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Intelligent building design based on green and low-carbon concept by Qian Lv

“…Guided by the concept of green and low-carbon, intelligent building design emphasizes the full utilization of renewable energy while utilizing advanced algorithms to optimize energy scheduling in intelligent buildings, achieving green, low-carbon, energy-saving, and emission-reduction goals. …”
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Iterative approach for photonic crystal devices design by Pavel V. Mokshin, Dimitriy L. Golovashkin, Vladimir S. Pavelyev

“…The proposed approach differs from known general-purpose optimization methods (e.g., genetic algorithm or gradient procedures) by using diffraction pattern information at different frequencies while optimizing an element designed to operate at the selected wavelength. …”
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A Knowledge-Driven Smart System Based on Reinforcement Learning for Pork Supply-Demand Regulation by Haohao Song, Jiquan Wang

“…By harnessing dynamic decision-making capabilities of reinforcement learning (RL), we design an optimization architecture centered on the Q-learning mechanism and dual-strategy pools, which is integrated into the honey badger algorithm to form the RL-enhanced honey badger algorithm (RLEHBA). …”
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