Coordinated Interaction Strategy of User-Side EV Charging Piles for Distribution Network Power Stability by Juan Zhan, Mei Huang, Xiaojia Sun, Zuowei Chen, Zhihan Zhang, Yang Li, Yubo Zhang, Qian Ai

“…The results show that the optimization strategy proposed by NSGA-II can increase the operating revenue of charging stations by 33.43% while reducing user energy costs and grid voltage deviations by 18.9% and 68.89%, respectively.…”
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Bayesian Time-Domain Ringing Suppression Approach in Impulse Ultrawideband Synthetic Aperture Radar by Xinhao Xu, Wenjie Li, Haibo Tang, Longyong Chen, Chengwei Zhang, Tao Jiang, Jie Liu, Xingdong Liang

“…Building on this analysis, we propose a Bayesian ringing suppression algorithm based on sparse optimization. The method effectively enhances imaging quality while balancing the trade-off between ringing suppression and image fidelity. …”
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Intelligent Design of Pavement Concrete Based on RSM-NSGA-III-CRITIC-VIKOR by Yuren Huo, Zhaoguang Li, Yan Wang

“…This study develops an integrated optimization framework combining Response Surface Methodology (RSM), Non-dominated Sorting Genetic Algorithm III (NSGA-III), Criteria Importance Through Intercriteria Correlation (CRITIC) weighting, and VIšekriterijumsko KOmpromisno Rangiranje (VIKOR) decision-making to optimize the mix proportions water–cement ratio (W/C), sand ratio, and an air-entraining agent (AEA) for sustainable pavement concrete. …”
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Research on Fire Detection of Cotton Picker Based on Improved Algorithm by Zhai Shi, Fangwei Wu, Changjie Han, Dongdong Song

“…The sensor measurements were compared with the actual values to verify the effectiveness of the GWO-PSO-optimized BP neural network model. Once experimentally verified, the improved GWO-PSO algorithm achieves a correlation coefficient R of 0.96929, a prediction accuracy rate of 96.10%, and a prediction error rate of only 3.9%, while the system monitors an accurate early warning rate of 96.07%, and the false alarm and omission rates are both less than 5%. …”
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Multijunction solar cell parameter estimation based on metaheuristic algorithms by Marwa M. Elzalabani, Doaa M. Atia, Aref Y. Eliwa, Belal A. Abou Zalam, Mahmoud S. AbouOmar

“…The study compared the performance of five optimization algorithms: Grey Wolf Optimizer (GWO), Artificial Hummingbird Algorithm (AHA), Tunicate Swarm Algorithm (TSA), War Strategy Algorithm (WSA), and Moth flam optimizer (MFO). …”
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Benchmarking Diffusion Annealing-Based Bayesian Inverse Problem Solvers by Evan Scope Crafts, Umberto Villa

“…The results provide insight into the strengths and limitations of existing diffusion-model based posterior samplers, while the benchmark problems provide a testing ground for future algorithmic developments.…”
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A Concise Review of Home Health Care Routing and Scheduling Problem by Soumen Atta, Vítor Basto-Fernandes, Michael Emmerich

“…The study examines various optimization approaches, including exact algorithms, heuristics, and metaheuristic techniques. …”
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An Innovative Priority-Aware Mission Planning Framework for an Agile Earth Observation Satellite by Guangtong Zhu, Zixuan Zheng, Chenhao Ouyang, Yufei Guo, Pengyu Sun

“…To address these challenges, this paper proposes a target clusters and dual-timeline optimization (TCDO) framework that integrates priority-based geographical clustering with temporal–spatial coordination mechanisms for efficient mission planning. …”
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Frame Theory and Fractional Programming for Sparse Recovery-Based mmWave Channel Estimation by Razvan-Andrei Stoica, Hiroki Iimori, Giuseppe Thadeu Freitas de Abreu, Koji Ishibashi

“…The first is a complete frame-theoretical treatment of the sensing matrix design (beam management) problem, compactly described by a pair of Lemmas that together with efficient low-coherence frame construction algorithms offer a general solution for the optimal transmitter (Tx) and receiver (Rx) beamforming components of the sparse mmWave channel estimation problem. …”
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AI-Driven Innovation in Skin Kinetics for Transdermal Drug Delivery: Overcoming Barriers and Enhancing Precision by Nubul Albayati, Sesha Rajeswari Talluri, Nirali Dholaria, Bozena Michniak-Kohn

“…Machine learning models trained on extensive molecular datasets predict skin permeability and accelerate the selection of suitable drug candidates. AI-driven algorithms optimize formulations, including penetration enhancers and advanced delivery technologies like microneedles and liposomes, while ensuring safety and efficacy. …”
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Streaming LiDAR Scene Flow Estimation by Mazen Abdelfattah, Z. Jane Wang, Rabab Ward

“…Furthermore, to enhance test-time optimization within our streaming framework, our novel initialization scheme ’warm-starts' the current optimization using optimized parameters from the preceding slice. …”
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Simplifying the calibration of ecological models by using the parameter estimation tool (PEST): The Curonian Lagoon case by Burak Kaynaroglu, Mindaugas Zilius, Rasa Idzelytė, Artūras Razinkovas-Baziukas, Georg Umgiesser

“…However, we challenged this assumption by initiating the inverse problem at different locations in the parameter space using a robust variant of a gradient-based method, which ultimately resulted in a better fit than global methods.We tested four different optimization algorithms available in the PEST and PEST++ suites. …”
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Machine learning-based prediction method for open-pit mining truck speed distribution in manned operation by Changyou XU, Gang CHEN, Qiuxia ZHANG, Bo WANG, Hongwang ZHANG, Hongrui LI, Weiwei QIN, Muyang LI

“…The purpose is to develop and apply a machine learning-based approach for the prediction and scheduling optimization of open-pit mining truck speeds. Open-pit mining is a significant method for coal mining, making it crucial to enhance the transportation efficiency of mining trucks. …”
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Research on Multi-Target Point Path Planning Based on APF and Improved Bidirectional RRT* Fusion Algorithm by Zijian Bian, Gang Li, Xizheng Wang

“…A multi-target point heuristic planning strategy is proposed to achieve shorter global paths while maintaining shorter local paths, taking into account both local solutions and optimal solutions, so that the fusion algorithm can be applied to the path planning of multi-target points.…”
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Solving Integer Ambiguity Based on an Improved Ant Lion Algorithm by Wuzheng Guo, Yuanfa Ji, Xiyan Sun, Xizi Jia

“…First, the performance of the SAALO algorithm was evaluated by comparing its solving speed and success rate with those of the Ant Lion Optimization Algorithm (ALO), the LAMBDA algorithm and the MLAMBDA algorithm. …”
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Application of Artificial Intelligence Computer Intelligent Heuristic Search Algorithm by Fanghai Gong

“…After 114 iterations of the heuristic search algorithm, the optimal value is 6.83353635e-001, while the average optimal value is 6.83551939e-001. …”
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Planning trajectory for UAVs using the self-organizing migrating algorithm. by Quoc Bao Diep, Thanh-Cong Truong, Ivan Zelinka

“…To optimize this cost function, we employ the self-organizing migrating algorithm, a swarm intelligence algorithm inspired by the cooperative and competitive behaviors observed in natural organisms. …”
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An Improved Small Target Detection Algorithm Based on YOLOv8s by G. Ma, C. Xu, Z. Xu, X. Song

“…To address these challenges, this pa¬per proposes an enhanced small object detection algorithm, SOD-YOLO, based on YOLOv8s. First, the S_C2f_CAFM module is integrated into the feature extraction network, enabling the effective capture of fine-grained local features and broad contextual information, while simultaneously reducing model parameters and computational complexity. …”
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Honeyword Generation Using a Proposed Discrete Salp Swarm Algorithm by Yasser A. Yasser, Ahmed T. Sadiq, Wasim AlHamdani

“…This work will present a novel honeyword generation method that uses a proposed discrete salp swarm algorithm. The salp swarm algorithm (SSA) is a bio-inspired metaheuristic optimization algorithm that imitates the swarming behavior of salps in their natural environment. …”
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Development of an Algorithm to Determine the Most Efficient Trajectories in Directional Wells by R.R. Francisco, M. Bertuzzi, G.V.V. Ramlov, L.A. Alves, C.E. Metzler

“…The primary goal is to optimize the trajectory by minimizing the tension and torques applied to the drill column during drilling operations while ensuring the well stability and operational efficiency. …”
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