A Forecasting Approach for Wholesale Market Agricultural Product Prices Based on Combined Residual Correction by Bo Li, Yuanqiang Lian

“…Initially, the sparrow search algorithm (SSA) is used to optimize the penalty factors and kernel parameters of support vector regression (SVR) and the input weights and hidden layer biases of the extreme learning machine (ELM), thereby improving the convergence rate and predictive accuracy of these models. …”
Get full text

Optimizing Vehicle Routing for Perishable Products with Time Window Constraints: by Rifqi Fauzi, Adi Priansyah, Paskalis Krisna Puspadewa, Syifa Maulvi Zainun Awal, Huu Tho Nguyen, Achmad Pratama Rifai

Get full text

Coordinated Reentry Guidance with A* and Deep Reinforcement Learning for Hypersonic Morphing Vehicles Under Multiple No-Fly Zones by Cunyu Bao, Xingchen Li, Weile Xu, Guojian Tang, Wen Yao

Get full text

Seasonally Adaptive VMD-SSA-LSTM: A Hybrid Deep Learning Framework for High-Accuracy District Heating Load Forecasting by Yu Zhang, Keyong Hu, Lei Lu, Qingqing Yang, Min Fang

“…The model establishes a dynamically adaptive forecasting framework through synergistic integration of the Sparrow Search Algorithm (SSA), Variational Mode Decomposition (VMD), and Long Short-Term Memory (LSTM) network. …”
Get full text

Research on dynamic prediction and optimization of high altitude photovoltaic power generation efficiency using GVSAO-CNN Model under 8-climate modes by Xiaoming Xiong, Heng Hu, Qiangfu Jia, Rongjian Zhang, Chongan Huang, Qingyuan Lu

“…The present study proposes a novel dynamic prediction model for high-altitude PV efficiency, namely the GVSAO-CNN, which combines the Gravity Search Optimization Algorithm (GVSAO). This algorithm, as detailed in a breakthrough patent for high-altitude PV data optimization, has been shown to enhance the accuracy of solar irradiance predictions by dynamically correcting model predictions with actual observational data and Convolutional Neural Network (CNN). …”
Get full text

Extending Conflict-Based Search for Optimal and Efficient Quadrotor Swarm Motion Planning by Zihao Wang, Zhiwei Zhang, Wenying Dou, Guangpeng Hu, Lifu Zhang, Meng Zhang

“…SL-CBS is a two-layer search algorithm: (1) The low-level search utilizes an improved state lattice. …”
Get full text

Differential Evolution-Based Transient Search Optimizer for Image Multi-Thresholding Problem by Nitin Mittal, Supreet Singh, Lalit Kumar, Gurpreet Kaur, Vikas Mittal, A. Johnson Santhosh

“…This research proposed a self-adaptive hybrid differential evolution (DE) based transient search optimizer (TSO) called DETSO. DETSO uses the search equations of DE algorithm to improve the exploration capability of original TSO. …”
Get full text

Evolutionary Search with Multiple Utopian Reference Points in Decomposition-Based Multiobjective Optimization by Wu Lin, Qiuzhen Lin, Zexuan Zhu, Jianqiang Li, Jianyong Chen, Zhong Ming

“…The use of these utopian points can prevent solutions to gather in the same region of PF and helps to strike a good balance of exploration and exploitation in the search space. The performance of our proposed algorithm is validated on tackling 16 recently proposed test problems with difficult-to-approximate PF boundaries and empirically compared to eight state-of-the-art multiobjective evolutionary algorithms. …”
Get full text

Intelligent UAV Map Generation and Discrete Path Planning for Search and Rescue Operations by Víctor San Juan, Matilde Santos, José Manuel Andújar

“…Search and Rescue Operations (SAR) take place in any emergency situation where people are involved and their lives are at risk. …”
Get full text

A novel variable neighborhood search approach for cell clustering for spatial transcriptomics by Aleksandra Djordjevic, Junhua Li, Shuangsang Fang, Lei Cao, Marija Ivanovic

“… This paper introduces a new approach to cell clustering using the Variable Neighborhood Search (VNS) metaheuristic. The purpose of this method is to cluster cells based on both gene expression and spatial coordinates. …”
Get full text

A Systematic Search of Distant Superclusters with the Subaru Hyper Suprime-Cam Survey by Tsung-Chi Chen, Yen-Ting Lin, Hsi-Yu Schive, Masamune Oguri, Kai-Feng Chen, Nobuhiro Okabe, Sadman Ali, Connor Bottrell, Roohi Dalal, Yusei Koyama, Rogério Monteiro-Oliveira, Rhythm Shimakawa, Tomotsugu Goto, Bau-Ching Hsieh, Tadayuki Kodama, Atsushi J. Nishizawa

“…Applying a friends-of-friends (FoF) algorithm to the CAMIRA cluster sample constructed using the Subaru Hyper Suprime-Cam survey data, we have conducted the first systematic search for superclusters at z = 0.5–1.0 and identified 673 supercluster candidates over an area of 1027 deg ^2 . …”
Get full text

Optimization of Restricted Container Relocation Using the Monte Carlo Tree Search Method by Chaabane Abdelali, Yachba Khadidja, Bellatreche Ladjel

“…The efficiency and relevance of this method are demonstrated through various solved scenarios and compared to a literature-based approach using genetic algorithms. …”
Get full text

DRAFTS: A Deep-learning-based Radio Fast Transient Search Pipeline by Yong-Kun Zhang, Di Li, Yi Feng, Chao-Wei Tsai, Pei Wang, Chen-Hui Niu, Hua-Xi Chen, Yu-Hao Zhu

“…The detection of fast radio bursts (FRBs) in radio astronomy is a complex task due to the challenges posed by radio-frequency interference and signal dispersion in the interstellar medium. Traditional search algorithms are often inefficient, time-consuming, and generate a high number of false positives. …”
Get full text

Improved grey wolf optimization algorithm based service function chain mapping algorithm by Yue ZHANG, Junnan ZHANG, Xiaochun WU, Chen HONG, Jingjing ZHOU

“…With the rise of new Internet applications such as the industrial Internet, the Internet of vehicles, and the metaverse, the network’s requirements for low latency, reliability, security, and certainty are facing severe challenges.In the process of virtual network deployment, when using network function virtualization technology, there were problems such as low service function chain mapping efficiency and high deployment resource overhead.The node activation cost and instantiation cost was jointly considered, an integer linear programming model with the optimization goal of minimizing the average deployment network cost was established, and an improved grey wolf optimization service function chain mapping (IMGWO-SFCM) algorithm was proposed.Three strategies: mapping scheme search based on acyclic KSP algorithm, mapping scheme coding and improvement based on reverse learning and nonlinear convergence were added to the standard grey wolf optimization algorithm to form this algorithm.The global search and local search capabilities were well balanced and the service function chain mapping scheme was quickly determined by IMGWO-SFCM.Compared with the comparison algorithm, IMGWO-SFCM reduces the average deployment network cost by 11.86% while ensuring a higher service function chain request acceptance rate.…”
Get full text

EV charging stations for sustainable urban transport electrification in the Arabian Peninsula: Performance assessment, social-economic aspects, opportunities, implementation challe... by Jamiu O. Oladigbolu, Asad Mujeeb, Mohd Bilal, Yusuf A. Al-Turki, Saleh S. Alharbi, Salah S. Alharbi

“…The effectiveness and innovation of HGWCSA are validated through comparative performance assessments against conventional metaheuristic algorithms. …”
Get full text

Model for selective vehicle problem considering mixed fleet with capacitated electric vehicles by Jiacheng Li, Masato Noto, Yang Zhang, Jia Guo

“…Subsequently, an adaptive large neighborhood search algorithm, improved on the basis of simulated annealing principles and local search algorithms, is proposed. …”
Get full text

Short-Term Power Load Prediction of VMD-LSTM Based on ISSA Optimization by Shuai Wu, Huafeng Cai

“…The Improved Sparrow Search Algorithm (ISSA), which integrates piecewise chaotic mapping into population initialization to augment the global exploration capability, is employed to fine-tune LSTM hyperparameters, thereby enhancing the prediction precision. …”
Get full text

A Deformation Prediction Model for Concrete Dams Based on RSA-VMD-AttLSTM by Pei Liu, Hao Gu, Chongshi Gu, Yanbo Wang

“…This paper presents a deformation prediction model for concrete dams that integrates a reptile search algorithm (RSA), a Variational Mode Decomposition (VMD) algorithm, and a long short-term memory network model with attention mechanism (AttLSTM). …”
Get full text

Hydrological and chemical characteristics of karst groundwater and carbon flux estimation by Qing Wang, Yin Zhang, Ningtao Wang, Mengru Li, Yu Zhang

“…A carbon flux estimation model was established by combining support vector machine regression and sparrow search algorithm to achieve groundwater carbon flux estimation. …”
Get full text

A novel research on network security situation prediction based on iteratively optimized RBF-NN by Yuqin Wu, Congqi Shen, Shungen Xiao, Wei Feng, Yexian Fan, Xiuzhuang Zhou

“…Moreover, we introduce a cross-model method with a genetic algorithm to compute the optimal weights for the RBF-NN model. …”
Get full text