Advancing Ton-Bag Detection in Seaport Logistics with an Enhanced YOLOv8 Algorithm by Xiulin Qiu, Haozhi Zhang, Chang Yuan, Qinghua Liu, Hongzhi Yao

“…Due to the problems of inaccurate ton bag identification, high costs, large model sizes, and long computation times in traditional freight transportation—issues that hinder meeting real-time requirements on resource-constrained operational equipment—this paper proposes an improved lightweight ton bag detection algorithm, YOLOv8-TB (YOLOv8-Ton Bag), which is optimized based on YOLOv8. …”
Get full text

Comprehensive Analysis of Lightweight Cryptographic Algorithms for Battery-Limited Internet of Things Devices by Nahom Gebeyehu Zinabu, Yihenew Wondie Marye, Kula Kekeba Tune, Samuel Asferaw Demilew

“…Among the main trends that were covered were the trade-offs between resource limitations and security strength, hardware–software co-optimization, block and stream cipher optimization, and hybrid encryption techniques. …”
Get full text

Optimal allocation of STATCOM for multi-objective ORPD problem on thermal wind solar hydro scheduling using driving training based optimization by Tushnik Sarkar, Sabyasachi Gupta, Chandan Paul, Susanta Dutta, Provas Kumar Roy, Anagha Bhattacharya, Ghanshyam G. Tejani, Seyed Jalaleddin Mousavirad

“…The Driving Training Based Optimization (DTBO) method has been used to achieve the goals, and its performance has been compared to that of other optimization algorithms that have been reported in recent ORPD studies. …”
Get full text

Algorithm study of digital HPA predistortion using one novel memory type BP neural network by Chun-hui HUANG, Yong-jie WEN

“…Based on the characteristic analysis of the high power amplifier (HPA) in wide-band CMMB repeater stations,a novel neural network was proposed which can respectively process the memory effect and the nonlinear of power amplifier.The novel model based on real-valued time-delay neural networks(RVTDNN) uses the Levenberg-Marquardt (LM) optimization to iteratively update the coefficients of the neural network.Due to the new parameters w⁰in the novel NN model,the modified formulas of LM algorithm were provided.Next，in order to eliminate the over-fitting of LM algorithm,the Bayesian regularization algorithm was applied to the predistortion system.Additionally,the predistorter of CMMB repeater stations based on the indirect learning method was constructed to simulate the nonlinearity and memory effect of HPA.Simulation results show that both the NN models can improve system performance and reduce ACEPR (adjacent channel error power ratio ) by about 30 dB.Moreover,with the mean square error less than 10⁻⁶,the coefficient of network for FIR-NLNNN is about half of that for RVTDNN.Similarly,the times of multiplication and addition in the iterative process of FIR-NLNNN are about 25% of that for RVTDNN.…”
Get full text

Syn-MolOpt: a synthesis planning-driven molecular optimization method using data-derived functional reaction templates by Xiaodan Yin, Xiaorui Wang, Zhenxing Wu, Qin Li, Yu Kang, Yafeng Deng, Pei Luo, Huanxiang Liu, Guqin Shi, Zheng Wang, Xiaojun Yao, Chang-Yu Hsieh, Tingjun Hou

“…Abstract Molecular optimization is a crucial step in drug development, involving structural modifications to improve the desired properties of drug candidates. …”
Get full text

Machine learning prediction and interpretability analysis of high-risk chest pain: a study from the MIMIC-IV database by Hongyi Chen, Haiyang Song, Hongyu Huang, Xiaojun Fang, Huang Chen, Qingqing Yang, Junyu Zhang, Wenjun Ding, Zheng Gong, Jun Ke

“…To address class imbalance, we implemented feature engineering with SMOTE and under-sampling techniques. Model optimization was performed via Bayesian hyperparameter tuning. …”
Get full text

Train adaptive energy saving strategy based on iterative induced genetic algorithm by MEI Wenqing, SHI Ke, ZHANG Zhengfang

“…Then, to overcome the difficulty of traditional genetic algorithms in solving continuous sub-interval optimization problems due to discrete independence, an iterative induced genetic algorithm was designed to calculate the Pareto optimal solution set for the energy-saving objective function. …”
Get full text

The necessity of the Black Sea region transport structure improvement by L.V. Nazarova

Get full text

A Detailed Comparison of Two New Heuristic Algorithms Based on Gazelles Behavior by Emine Baş

“…In this study, Mountain Gazelle Optimization (MGO) and Gazelle Optimization Algorithm (GOA) algorithms, which have been newly proposed in recent years, were examined. …”
Get full text

Energy scheduling algorithm for urban rail active traction power supply system by ZHANG Chao, LI Hongbo, ZHAO Liying, HUANG Zihao, LUO Wenguang, WANG Xiong

“…The full power and constant voltage models were used to simulate the two different working conditions of the bidirectional converter, and the internal and external double-layer iterative algorithm was used to calculate the power flow. …”
Get full text

A Review on Path Planning and Obstacle Avoidance Algorithms for Autonomous Mobile Robots by Anis Naema Atiyah Rafai, Noraziah Adzhar, Nor Izzati Jaini

“…This paper reviews the mobile robot navigation approaches and obstacle avoidance used so far in various environmental conditions to recognize the improvement of path planning strategists. Taking into consideration commonly used classical approaches such as Dijkstra algorithm (DA), artificial potential field (APF), probabilistic road map (PRM), cell decomposition (CD), and meta-heuristic techniques such as fuzzy logic (FL), neutral network (NN), particle swarm optimization (PSO), genetic algorithm (GA), cuckoo search algorithm (CSO), and artificial bee colony (ABC). …”
Get full text

Application of artificial intelligence technology in the economic development of urban intelligent transportation system by Ziming Zhao, Jinyu Chen

“…A traffic flow prediction model was established for traffic flow prediction and optimized scheduling algorithms were used to dispatch vehicles on congested urban roads intelligently. …”
Get full text

Research on short-term precipitation forecasting method based on CEEMDAN-GRU algorithm by Hua Xu, Zongkai Guo, Yu Cao, Xu Cheng, Qiong Zhang, Dan Chen

Get full text

Optimizing power network expansion with pumped hydro energy storage using a multi-objective enhanced spider wasp optimizer approach by Mohamed M. Refaat, Saad F. Al-Gahtani, Hussain Bassi, Ziad M. Ali, Shady H. E. Abdel Aleem

“…The problem is framed as a comprehensive multi-objective optimization model designed to minimize the cost of network expansion while maximizing the benefits of integrating various PHES technologies. …”
Get full text

Energy-efficient collaborative transmission algorithm based on potential game theory for beamforming by Jing Zhang, Li Lei, Xin Feng

“…Second, a potential game model is proposed as a joint method for optimizing the collaborative parameters of the cooperative nodes and their energy consumption balancing features. …”
Get full text

Toward an algorithm of percutaneous microelectrolysis: a randomized clinical trial on invasive techniques by Carlos Eduardo Girasol, Nathaly Escobar Durán, Santiago Marcelo D’Almeida, Oscar Ariel Ronzio

“…CONCLUSIONS: All needling techniques demonstrated analgesic effects on myofascial trigger points, with the algorithm-enhanced MEP showing the most notable improvement in self-reported pain. …”
Get full text

Multi-Task Perception Algorithm for Rail Transit Scenarios Based on Triplet Attention by GAO Rui, XIONG Yanping, WEI Chenfeng, XIE Guotao, GAO Ming

“…Through validation using datasets from actual scenes, the model exhibited significant improvements in small object detection, detection speed, and environmental adaptability. …”
Get full text

Storage Assignment Optimization in Robotic Mobile Fulfillment Systems by Ruiping Yuan, Juntao Li, Wei Wang, Jiangtao Dou, Luke Pan

“…A two-stage hybrid algorithm combining greedy algorithm and improved simulated annealing is designed to solve the model. …”
Get full text

Image Reconstruction Algorithm Based on Extreme Learning Machine for Electrical Capacitance Tomography by SU Ziheng, CHEN Deyun, WANG Lili

“…Aiming at the problem that the traditional ECT is not accurate in complex situations, this paper proposes a depth learning based inversion method Through the improvement and optimization of the traditional extreme learning machine, the image feature information obtained by the reconstructed image method is used as the training data, and the result obtained by inputting the data into the predictive model is used as the prior information The cost function is used to encapsulate the prior knowledge and domain expertise, and spatial regularizers and time regularizers are introduced to enhance sparsity The separated Bregman (SB) algorithm and the iterative shrinkage threshold (FIST) method are used to solve the specified cost function The final imaging result is obtained The simulation results show that the image reconstructed by this method has less than 10% error compared with the original flow pattern, and reduces artifacts and distortion, which improves the reconstructed image quality…”
Get full text

A hybrid Spatial Ant Lion optimization and utilitarian data transmission approach for intelligent optimization for energy-efficient wireless sensor networks by Malathy Sathyamoorthy, Rajesh Kumar Dhanaraj, C N Vanitha, Md Shohel Sayeed

“…Results demonstrate that the proposed model achieved a 1.86% increase in throughput, a 2.56% reduction in delay, and a 3.18% improvement in energy efficiency when compared to existing schemes such as PSO, ALO, and SA-AOA.…”
Get full text