Relocation Optimization for Shared Electric Vehicles: A Literature Review by Ye Zou, Qian Yu, Dongming Jiang, Youjun Deng

“…Static relocation is analyzed in terms of operator-based relocation and user-based relocation, while dynamic relocation is analyzed in terms of four methodologies: optimization models, simulations, multi-stage methods, and deep reinforcement learning. …”
Get full text

Unlocking the power of antimicrobial peptides: advances in production, optimization, and therapeutics by Mohd Sadeeq, Yu Li, Chaozhi Wang, Feifei Hou, Jia Zuo, Peng Xiong

“…Furthermore, we underscore the transformative role of artificial intelligence, particularly machine learning algorithms, in accelerating AMP discovery and optimization, thereby propelling their expanded therapeutic application and contributing to the global fight against drug-resistant infections.…”
Get full text

OPTIMIZING KEYWORD SEARCH FOR SEARCH ENGINES USING BLOCKCHAIN TECHNOLOGY by Bharti Aggarwal, Dinesh Rai, Naresh Kumar

“…The multifaceted evaluation, employing TF-IDF and cosine similarity across three datasets, demonstrates the efficacy of this approach in optimizing website visibility while safeguarding user data. …”
Get full text

Optimizing Container Placement in Data Centers by Deep Reinforcement Learning by Hyeonjeong Kim, Cheolhoon Lee

“…Specifically, we utilize deep reinforcement learning (DRL), which has been widely applied in various fields, to optimize container placement. Our approach outperforms traditional heuristic algorithms and offers the additional advantage of handling fixed-size inputs, enabling flexible operation regardless of the number of containers. …”
Get full text

Fair Probabilistic Multi-Armed Bandit With Applications to Network Optimization by Zhiwu Guo, Chicheng Zhang, Ming Li, Marwan Krunz

“…To address the FP-MAB problem, we propose two algorithms: Fair Probabilistic Explore-Then-Commit (FP-ETC) and Fair Probabilistic Optimism In the Face of Uncertainty (FP-OFU). …”
Get full text

Multiradar Collaborative Task Scheduling Algorithm Based on Graph Neural Networks with Model Knowledge Embedding by Haoqing LI, Dian YU, Changchun PAN, Wenxian YU, Dongying LI

“…A key innovation of this algorithm is its capability to capture critical model knowledge using low-complexity calculations, which helps to further optimize the GNN model. …”
Get full text

Optimized window functions for spectral analysis based on digital filters by R.V. Petrosian

“…The article addresses a relevant issue of improving the accuracy of spectral analysis in computerized systems by optimizing window functions used in the Discrete Fourier Transform (DFT). …”
Get full text

Energy Efficiency Optimization in Swarm Robotics for Smart Photovoltaic Monitoring by Dimitris Ziouzios, Nikolaos Baras, Minas Dasygenis, Vayos Karayannis, Constantinos Tsanaktsidis

Get full text

Optimizing Personalized and Context-Aware Recommendations in Pervasive Computing Environments by A. C. Kaladevi, V. Vinoth Kumar, T. R. Mahesh, Suresh Guluwadi

“…Reinforcement learning algorithms optimize the recommendation policy based on user feedback. …”
Get full text

Integrating Mobile Devices and Wearable Technology for Optimal Sleep Conditions by You-Kwang Wang, Chien-Yu Chen

“…This project uses cloud storage technology and cloud software algorithms to enable data sharing and real-time feedback. …”
Get full text

Genetic Algorithm and Mathematical Modelling for Integrated Schedule Design and Fleet Assignment at a Mega-Hub by Melis Tan Tacoglu, Mustafa Arslan Ornek, Yigit Kazancoglu

“…Second, a genetic algorithm (GA) was employed to demonstrate scalability and flexibility, delivering near-optimal, high-granularity schedules with significantly reduced computational time. …”
Get full text

An energy-saving virtual machine scheduling algorithm for resource management based on cloud computing technology by Liangyu Zhang

“…Therefore, the algorithm proposed in this paper can effectively reduce energy consumption while avoiding frequent migration of virtual machines, and the innovation in genetic algorithm optimization strategy improves the overall efficiency and stability of scheduling.…”
Get full text

Review on Maximum Power Point Tracking Control Strategy Algorithms for Offshore Floating Photovoltaic Systems by Lei Huang, Baoyi Pan, Shaoyong Wang, Yingrui Dong, Zihao Mou

“…This paper provides a thorough review of MPPT techniques applicable to floating photovoltaic systems, evaluating the suitability of various methods under marine conditions. Traditional algorithms require modifications to address the drift phenomena under uniform irradiation, while different GMPPT techniques exhibit distinct strengths and limitations in partial shading conditions (PSCs). …”
Get full text

Combining the A* Algorithm with Neural Networks to Solve the Team Orienteering Problem with Obstacles and Environmental Factors by Alfons Freixes, Javier Panadero, Angel A. Juan, Carles Serrat

“…To achieve this, we employ a simheuristic algorithm for the overall route optimization, while integrating the A* algorithm to determine feasible paths between nodes that avoid obstacles in a 2D grid-based environment. …”
Get full text

Quantitative study on weak magnetic detection defects of metal structure based on IWOA-BP algorithm by FAN Meng, TONG Bo, GAO Chen, YAO Zhongyuan, ZHANG Yu, HU Bo

“…In view of the poor effect and low efficiency of BP neural network in parameter adjustment, the improved whale optimization algorithm (IWOA) based on Sine chaotic mapping was adopted to optimize the BP neural network parameter adjustment mode, giving consideration to global optimization while improving the local optimization ability, and then the optimal parameters searched by IWOA were assigned to BP neural network, improving the quality of initial network parameters.The length, width and depth of the artificial rectangular slot were quantified by inversion. …”
Get full text

Disease Detection Algorithm for Tea Health Protection Based on Improved Real-Time Detection Transformer by Zhijie Lin, Zilong Zhu, Lingling Guo, Jingjing Chen, Jiyi Wu

“…Faster-LTNet employs partial convolution and hierarchical design to optimize computational resources, while the CG Attention Module enhances multi-head self-attention by introducing grouped feature inputs and cascading operations to reduce redundancy and increase attention diversity. …”
Get full text

Enhanced electric vehicle battery management system employing bat algorithm with chaotic diversification strategies by Batchu Veena Vani, Dharavath Kishan, Md Waseem Ahmad, Ch. Rama Prakasha Reddy

“…This article presents a method using the Bat Algorithm (BA) improved by chaotic diversification as well as social education to optimize the power source replacement and the electric vehicle charging procedure. …”
Get full text

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. …”
Get full text

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. …”
Get full text

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.…”
Get full text