MGL-YOLO: A Lightweight Barcode Target Detection Algorithm by Yuanhao Qu, Fengshou Zhang

“…Finally, a Lightweight Shared Multi-Scale Detection Head (LSMD) is proposed, which improves the model’s detection accuracy and adaptability while reducing the model’s parameter size and computational complexity. …”
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A Bi-Layer Collaborative Planning Framework for Multi-UAV Delivery Tasks in Multi-Depot Urban Logistics by Junfu Wen, Fei Wang, Yebo Su

“…The upper layer tackles the task assignment problem by formulating a multi-objective optimization model aimed at minimizing economic costs, delivery delays, and the number of UAVs deployed. …”
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Research on Multi-Objective Coordinated Planning of Distribution Networks Based on Improved Generative Adversarial Networks by Li Zhu

“…Next, a bi-level distribution network planning model considering carbon footprints is established: the upper level minimizes the annual comprehensive cost by optimizing the planning schemes of distributed generation (DG), energy storage systems (ESS), and capacitor banks (CB); the lower level minimizes operating costs, voltage deviations, and carbon emissions by formulating operation strategies under typical scenarios, considering on-load tap changers (OLTC), controllable loads, capacitor banks, energy storage, and distributed generation. …”
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The Use of Artificial Intelligence Technologies in Energy and Climate Security by Igbal A. Guliev, Agil Mammadov, Kanan Ibrahimli

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A Method for Service Function Chain Migration Based on Server Failure Prediction in Mobile Edge Computing Environment by Joelle Kabdjou, Norihiko Shinomiya

“…Using a Long Short-Term Memory (LSTM) algorithm optimized by Super SAPSO (Simulated Annealing Particle Swarm Optimization), the model forecasts server failures with improved accuracy, reducing False Alarm Rates and improving Failure Detection Rates. …”
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A High-Performance and Lightweight Maritime Target Detection Algorithm by Shidan Sun, Zhiping Xu, Xiaochun Cao, Jiachun Zheng, Jiawen Yang, Ni Jin

“…The experimental results show that the proposed algorithm can achieve a nearly 10 percent mean average precision value improvement with nearly half the model size, compared with counterparts. …”
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An Efficient Resource Allocation Algorithm for Task Offloading in the Internet of Vehicles by Ahmad Salehi, Sadoon Azizi

“…Simulation results demonstrate that the proposed algorithm reduces memory costs and penalties from rejected tasks, while improving overall system profit. …”
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Radial Basis Function Coupling with Metaheuristic Algorithms for Estimating the Compressive Strength and Slump of High-Performance Concrete by Amir Reza Taghavi Khangah, Erfan Khajavi, Hasti Azizi, Amir Reza Alizade Novin

“…These are indicative of the accuracy and reliability of the RBWG model in modelling the properties of HPC. This work's significance consists of improving the concrete mix design by giving correct predictions of HPC performance, which will lead to optimized resource utilization, minimized costs, and reduced negative environmental impacts due to construction. …”
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Application of Artificial Intelligence Algorithms in the Field of Antimicrobial Peptide Prediction by QIAN Yuchen, NIE Ting, HUA Yanming, XU Shiying, GUO Sheng, ZHANG Xin, LUO Xiaohu, LIU Yanan

“…Artificial intelligence algorithms can be continuously optimized based on prior knowledge and real-time data, which significantly improves the prediction efficiency of antibacterial peptides and reduces research and development costs. …”
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Improved Splitting-Integrating Methods for Image Geometric Transformations: Error Analysis and Applications by Hung-Tsai Huang, Zi-Cai Li, Yimin Wei, Ching Yee Suen

“…The splitting-integrating method (SIM) is well suited to the inverse transformation <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mi>T</mi><mrow><mo>−</mo><mn>1</mn></mrow></msup></semantics></math></inline-formula> of digital images and patterns, but it encounters difficulties in nonlinear solutions for the forward transformation <i>T</i>. We propose improved techniques that entirely bypass nonlinear solutions for <i>T</i>, simplify numerical algorithms and reduce computational costs. …”
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Design and energy management research of integrated microgrid with light storage and charging with double-layer optimization scheduling model by Pan Zhai

“…On the basis of considering user needs, a time of use electricity pricing scheduling control strategy is proposed to achieve control over energy flow, and an improved particle swarm algorithm is used to handle the objective function. …”
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Improved deep learning model for accurate energy demand prediction and conservation in electric vehicles integrated with cognitive radio networks by V. Niranjani, Anandakumar Haldorai

“…To overcome this issue, this paper proposed a model of Empirical Mode Decomposition with CNN and optimized with Seagull Optimization Algorithm (EMD-CNN-SOA). …”
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Application of the Bidirectional Encoder Representations from Transformers Model for Predicting the Abbreviated Injury Scale in Patients with Trauma: Algorithm Development and Vali... by Jun Tang, Yang Li, Keyu Luo, Jiangyuan Lai, Xiang Yin, Dongdong Wu

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Adaptive Differential Evolution Algorithm for Forward Position Solution of Parallel Mechanism by Yi Jian

“…According to the constrained length of the bars,the unconstrained optimization model is constructed to formulate the forward position analysis for a 6 degrees-of-freedom general 6-SPS parallel mechanism,and the differential evolution（ DE） algorithm is employed to solve this problem. …”
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Artificial Intelligence-Driven Approach to Optimizing Boiler Power Generation Efficiency: The Advanced Boiler Combustion Control Model by Kyu-Jeong Lee, So-Won Choi, Eul-Bum Lee

“…Consequently, achieving stable combustion control of these gases is critical for improving boiler efficiency. This study developed the advanced boiler combustion control model (ABCCM) by combining the random forest (RF) and classification and regression tree (CART) algorithms to optimize the combustion of steam power boilers using steel by-product gases. …”
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Intelligent Optimized Combined Model Based on GARCH and SVM for Forecasting Electricity Price of New South Wales, Australia by Yi Yang, Yao Dong, Yanhua Chen, Caihong Li

“…In this paper, we propose an optimized combined forecasting model by ant colony optimization algorithm (ACO) based on the generalized autoregressive conditional heteroskedasticity (GARCH) model and support vector machine (SVM) to improve the forecasting accuracy. …”
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Precise wind allocation scheme decision based on attraction-repulsion algorithm by NI Jingfeng, CHEN Dunwei, LIU Yujiao

“…Performance test results showed that AROA had a significant advantage in comprehensive optimization performance compared to Genetic Algorithm (GA), Simulated Annealing-Improved Particle Swarm Optimization (SA-IPSO), and Monotonic Basin Hopping (MBH). …”
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EPRSA: interference resource scheduling algorithms for air-ground communication networks by Wenpeng Wu, Zhenhua Wei, Haiyang You, Xiaoqing Li, Jianwei Zhan, Zhaoguang Zhang

“…Strategies such as cycle and initial quantity selection, elastic initialization, double tabu power scheduling, and jammer conversion are designed to improve the scheduling ability of the Elastic Parallel Random Search Algorithm (EPRSA) in terms of system operation duration and interference cost. …”
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Parametric Optimization of Train Brake Pad Using Reverse Engineering with Digital Photogrammetry 3D Modeling Method by P Paryanto, Muhammad Faizin, R Rusnaldy

“…This was followed by processing 2D images using Agisoft Metashape 2.2.1 software and Artificial Intelligence (AI) algorithms to create a precise 3D model. Subsequently, assessment was performed using feasibility in terms of cost, time, and accuracy. …”
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AI-Based Classification Model for Low-Energy Buildings: Promoting Sustainable Economic Development of Smart Cities With Spherical Fuzzy Decision Algorithm by Lin Yang

“…AI-based classification models for low-energy buildings are essential in promoting the economic development of smart cities by optimizing energy use, reducing operational costs, and enhancing overall efficiency. …”
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