Novel algorithm for multifocus image fusion: integration of convolutional neural network and partial differential equation by Gargi J Trivedi, Rajesh Sanghvi

“…Furthermore, we aim to enhance our approach by incorporating machine learning techniques to optimize the parameters of the image fusion algorithm. …”
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Grey Wolf Optimization- and Particle Swarm Optimization-Based PD/I Controllers and DC/DC Buck Converters Designed for PEM Fuel Cell-Powered Quadrotor by Habibe Gursoy Demir

“…Both optimizers work together in the system and try to minimize tracking errors while also minimizing power consumption by using suitable objective functions. …”
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Lightweight Transformer traffic scene semantic segmentation algorithm integrating multi-scale depth convolution by Gang XIE, Quanyi WANG, Xinlin XIE, Jian’an WANG

“…Aiming at the problems of discontinuous segmentation of thin strip objects that were easy to blend into the surrounding background and a large number of model parameters in the semantic segmentation algorithm of traffic scenes, a lightweight Transformer traffic scene semantic segmentation algorithm integrating multi-scale depth convolution was proposed.First, a multi-scale strip feature extraction module (MSEM) was constructed based on deep convolution to enhance the representation ability of thin strip target features at different scales.Secondly, a spatial detail auxiliary module (SDAM) was designed using the convolutional inductive bias feature in the shallow network to compensate for the loss of deep spatial detail information to optimize object edge segmentation.Finally, an asymmetric encoding-decoding network based on the Transformer-CNN framework (TC-AEDNet) was proposed.The encoder combined Transformer and CNN to alleviate the loss of detail information and reduce the amount of model parameters; while the decoder adopted a lightweight multi-level feature fusion design to further model the global context.The proposed algorithm achieves the mean intersection over union (mIoU) of 78.63% and 81.06% respectively on the Cityscapes and CamVid traffic scene public datasets.It can achieve a trade-off between segmentation accuracy and model size in traffic scene semantic segmentation and has a good application prospect.…”
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Short-Term Electric Load Forecasting for an Industrial Plant Using Machine Learning-Based Algorithms by Oğuzhan Timur, Halil Yaşar Üstünel

“…The integration of calendar, meteorological, and lagging electrical variables, along with machine learning-based algorithms, is employed to boost forecasting accuracy and optimize energy utilization. …”
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GVDF-RRT*: An Improved F-RRT* Path Planning Algorithm Based on Generalized Voronoi Diagram by Yitao Zhong, Xiaojing Zhu, Jianfang Huang, Yaokun Ye, Zhaoming Wang, Yuhuai Wang

“…Secondly, a node direct connection mechanism is established, which reduces the redundant computation and further reduces the initial time by hierarchical processing of creation nodes, while combined with the forward optimization mechanism to optimize the paths in iteration, effectively reducing the path cost. …”
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Reliable and efficient magnetic data inversion for resource detection using a hybrid bat algorithm by Khalid S. Essa, Mahmoud Elhussein, Omar A. Gomaa, Zein E. Diab

“…This study introduces an innovative hybrid algorithm integrating the Bat Algorithm (BA) with the Fourth Horizontal Gradient (FHG) to optimize the estimation of geometric parameters (depth, amplitude coefficient, shape factor, source origin, and magnetization angle) from magnetic field data. …”
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Enhancing Youbike Redistribution System: A Study on Station Recommendation Using a Genetic Algorithm by Yang-Chou Juan, Yi-Chung Chen, Wei-Ting Chen, Chieh Yang, Chia-Tzu Liu, Yi-Ci Hou, Yi-Hsuan Tsai

“…A random forest model selected key crowd grid factors as input variables for a long short-term memory (LSTM) prediction model to accurately predict demand patterns, including during special events or weather changes. A genetic algorithm then determined optimal station configurations and provided return station recommendations, considering user destinations and station dock ratios, while minimizing manual redistribution. …”
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A narrative review of surgical approaches in cervical degenerative myelopathy and update of the algorithm for decision making by Majid Reza Farrokhi, Seyed Reza Mousavi, Abbas Khosravifarsani, Jaloliddin Mavlonov, Mohammadhadi Amir Shahpari Motlagh, Seyed Bahram Seif, Armin Akbarzadeh

“…Personalized surgical planning is essential to optimize outcomes in CDM management.…”
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The A3C Algorithm With Eligibility Traces of Energy Management for Plug-In Hybrid Electric Vehicles by Dingyi Guo, Guangyin Lei, Huichao Zhao, Fang Yang, Qiang Zhang

“…A mathematical formulation of the energy management problem is proposed to optimize fuel consumption while adhering to the vehicle’s operational constraints. …”
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A Novel Energy Replenishment Algorithm to Increase the Network Performance of Rechargeable Wireless Sensor Networks by Tariq, Vishwanath Eswarakrishnan, Adil Hussain, Zhu Wei, Muhammad Uzair

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BED-YOLO: An Enhanced YOLOv10n-Based Tomato Leaf Disease Detection Algorithm by Qing Wang, Ning Yan, Yasen Qin, Xuedong Zhang, Xu Li

“…In recent years, object detection algorithms have gained widespread application in tomato disease detection due to their efficiency and accuracy, providing reliable technical support for crop disease identification. …”
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A Novel Two-Stage Learning-Based Phase Unwrapping Algorithm via Multimodel Fusion by Chao Yan, Tao Li, Yandong Gao, Shijin Li, Xiang Zhang, Xuefei Zhang, Di Zhang, Huiqin Liu

“…To solve this problem, this paper combines a deep neural network model with the traditional PhU model and proposes a novel two-stage learning-based phase unwrapping (TLPU) algorithm via multimodel fusion. The major advantages of TLPU are as follows: 1) A high-resolution U-Net (HRU-Net) model trained on a dataset constructed according to InSAR interferometric geometry is utilized for the PhU for the first time, which effectively improves the performance of the DLPU. 2) TLPU utilizes the traditional PhU method to optimize the results of DLPU, addressing the issue of weak generalization ability of a single DLPU, while improving accuracy in areas with large-gradient changes. …”
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Impact of an improved random forest-based financial management model on the effectiveness of corporate sustainability decisions by Jianhui Zhang

“…With the development of the economy, more and more electronic manufacturing enterprises are emerging like mushrooms after rain. These enterprises, while developing, also face financial risks caused by various reasons. …”
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Integrating Large Language Models and Optimization in Semi- Structured Decision Making: Methodology and a Case Study by Gianpaolo Ghiani, Gianluca Solazzo, Gianluca Elia

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DECISION TREE WITH HILL CLIMBING ALGORITHM BASED SPECTRUM HOLE DETECTION IN COGNITIVE RADIO NETWORK by N Suganthi, R Meenakshi, A Sairam, M Parvathi

“…The objective of the DTHC method is to improve detection accuracy while minimizing false alarm rates. The approach integrates a Decision Tree (DT) algorithm for rapid initial classification of Primary User (PU) activity, followed by a Hill Climbing (HC) optimization algorithm that fine-tunes the detection based on a fitness function. …”
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Solving the Problem of Vehicle Routing Problem With Time Window via Dual Adaptive Genetic Algorithm by Chunge Hua

“…To address the Vehicle Routing Problem with Time Windows (VRPTW), this paper presents a novel Dual Adaptive Genetic Algorithm (DAGA). While numerous metaheuristic algorithms have been proposed to solve VRPTW, most existing approaches either rely on fixed cost functions or incorporate local search heuristics without adaptive control. …”
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A PSO-Based Approach for the Optimal Allocation of Electric Vehicle Parking Lots to the Electricity Distribution Network by Marzieh Sadat Arabi, Anjali Awasthi

“…Using the particle swarm optimization (PSO) algorithm, the study maximizes total benefits, taking into account network parameters, vehicle data, and market prices. …”
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YOLOv8A-SD: A Segmentation-Detection Algorithm for Overlooking Scenes in Pig Farms by Yiran Liao, Yipeng Qiu, Bo Liu, Yibin Qin, Yuchao Wang, Zhijun Wu, Lijia Xu, Ao Feng

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Impact of surrogate model accuracy on performance and model management strategy in surrogate-assisted evolutionary algorithms by Yuki Hanawa, Tomohiro Harada, Yukiya Miura

“…Surrogate-assisted evolutionary algorithms (SAEAs) are widely used to solve expensive optimization problems where evaluating candidate solutions is computationally intensive. …”
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A Hybrid Algorithm for PMLSM Force Ripple Suppression Based on Mechanism Model and Data Model by Yunlong Yi, Sheng Ma, Bo Zhang, Wei Feng

“…Experiments show that the hybrid framework effectively compensates the unmodeled disturbance through the data model while maintaining the physical interpretability of the mechanistic model, which provides a new idea for motor performance optimization under complex working conditions.…”
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