A novel solid waste instance creation for an optimized capacitated vehicle routing model using discrete smell agent optimization algorithm by Ahmed T. Salawudeen, Olusesi A. Meadows, Basira Yahaya, Muhammed B. Mu'azu

“…The developed model was optimized using a new discrete smell agent optimization (SAO) algorithm and compared to firefly algorithm (FA) and particle swarm optimization (PSO). …”
Get full text

A new type of sustainable operation method for urban rail transit: Joint optimization of train route planning and timetabling by Guorong Fan, Chao Li, Xinyun Shao, Fangzheng Zhen, Yao Huang

“…A linearization method for the model is proposed. To solve large-scale problems, an improved adaptive large neighborhood search algorithm (ALNS) is designed accordingly. …”
Get full text

An improved Harris hawks optimizer with enhanced logarithmic spiral and dynamic factor and its application for predicting molten iron temperature in the blast furnace by Zhendong Liu, Yiming Fang, Le Liu, Shuidong Ma

“…Subsequently, IHHO‐ELSDF is subjected to a comparative analysis with 17 algorithms on the IEEE CEC2022 benchmark suite. These tests show that IHHO‐ELSDF outperforms most competitors in numerical optimization. …”
Get full text

Improving lifetime of WSN using modified Moth Flame Optimization by Methaq Mahdi Ali, Razieh Asgarnezhad

Get full text

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

“…To address the challenges of fluctuating power loads and inaccurate predictions by conventional methods, this paper presents a novel hybrid framework combining Variational Mode Decomposition (VMD), Long Short-Term Memory (LSTM), and the Improved Sparrow Search Algorithm (ISSA). First, the power load series is decomposed into intrinsic mode functions (IMFs) via VMD, where the optimal decomposition order K is determined using permutation entropy (PE). …”
Get full text

Alzheimer’s Disease Prediction Using Fisher Mantis Optimization and Hybrid Deep Learning Models by Sameer Abbas, Mustafa Yeniad, Javad Rahebi

Get full text

Classification and Recognition Method for Bearing Fault based on IFOA-SVM by Wei Zhang, Zhihua Ma

Get full text

Optimal scheduling method for multi-regional integrated energy system based on dynamic robust optimization algorithm and bi-level Stackelberg model by Bo Zhou, Erchao Li, Wenjing Liang

“…Finally, a combination algorithm of improved robust optimization over time (ROOT) and CPLEX is proposed to solve the established game model. …”
Get full text

Optimization of power output in plateau photovoltaic power stations using a hybrid Kepler and Gaussian quantum particle swarm algorithm by Shuang Gan, Heng Hu, Shaoshuai Li, Qian Peng, Taidong Yan, Huasheng Gong, Yuancheng Zhang

“…The proposed solution integrates the Kepler Optimization Algorithm (KOA) with the Gaussian Quantum Improved Particle Swarm Optimization (GQPSO) to address multi-objective optimization, with the goal of maximizing power generation, minimizing operational costs, and enhancing system stability. …”
Get full text

An Interpretable Data-Driven Dynamic Operating Envelope Calculation Method Based on an Improved Deep Learning Model by Yun Li, Tunan Chen, Jianzhao Liu, Zhaohua Hu, Yuchen Qi, Ye Guo

Get full text

Energy-Saving Optimization of HVAC Systems Using an Ant Lion Optimizer with Enhancements by Bin Hu, Yuhu Guo, Wenjun Huang, Jianxiang Jin, Mingxuan Zou, Zhikun Zhu

“…In this model, the energy-saving optimization effects of various advanced swarm intelligence optimization algorithms were compared. …”
Get full text

Taylor-Spotted Cat Optimization (Taylor-SCO): An Energy-Efficient Cluster Head Selection Algorithm with Improved Trust Factor for Data Routing in WSN by Shivaraj Kalburgi, M. Manimozhi

Get full text

An Improved Low-Bit-Rate Image Compression Framework Based on Semantic-Aware Model and Neighborhood Attention by Chengbin Zeng, Liang Zhang

“…In future work, we plan to improve the model’s robustness under low-light conditions and enhance compression efficiency through lightweight optimization techniques, enabling broader real-world deployment.…”
Get full text

A Data Resource Trading Price Prediction Method Based on Improved LightGBM Ensemble Model by Wan Nie, Bingliang Shen, Desheng Li

“…To address the key challenges of limited practical application, high implementation difficulty, and poor generalization capability in existing theoretical models for data resource pricing, this study employs generative adversarial network (GAN) to augment the dataset and constructs a DRV-LightGBM model based on a Bayesian parameter optimization algorithm that maximizes the coefficient of determination (<inline-formula> <tex-math notation="LaTeX">$R^{2}$ </tex-math></inline-formula>) to predict data resource transaction prices and provide post-hoc explanations for the prediction model. …”
Get full text

Comparative Performance Analysis of Optimization Algorithms in Artificial Neural Networks for Stock Price Prediction by Ekaprana Wijaya, Moch. Arief Soeleman, Pulung Nurtantio Andono

“…This study lays the groundwork for future research by suggesting the exploration of additional optimization algorithms and more complex neural network architectures to further improve prediction accuracy.…”
Get full text

Multi-Objective Optimization of Speed Profile for Railway Catenary Maintenance Vehicle Operations Based on Improved Non-Dominated Sorting Genetic Algorithm III by Bingli Zhang, Gan Shen, Yixin Wang, Yangyang Zhang, Chengbiao Zhang, Xinyu Wang, Zhongzheng Liu, Xiang Luo

“…Initially, a multi-objective optimization model is developed based on a four-stage operational strategy. …”
Get full text

Research on trajectory planning method for food sorting robot based on machine vision and improved BOA by CUI Wei, YUAN Rui, SUN Litao, WANG Wei

“…By improving the butterfly optimization algorithm, the optimal solution for the motion trajectory of the parallel robot was obtained and its superiority was verified.ResultsCompared with conventional methods, the proposed trajectory optimization method had better operational efficiency and control effects, with the more smoother of the planned trajectory. …”
Get full text

Hierarchical Deep Learning Model Optimization Using Enhanced Evolutionary-based Approach for Fake News Detection by Deepti Nikumbh, Anuradha Thakare

“…In comparison to manually designed HDLM, the proposed approach achieves up to 97.86% model compression with a 0.34% accuracy improvement, while a variant achieves 96.24% compression with a 0.23% accuracy improvement. …”
Get full text

Grouping control of electric vehicles based on improved golden eagle optimization for peaking by Yang Yu, Yuhang Huo, Shixuan Gao, Qian Wu, Mai Liu, Xiao Chen, Xiaoming Zheng, Xinlei Cai

“…First, considering the difference between peak and valley loads and the operating costs of EVs, a peak shaving model for EVs is constructed. Second, the design of IGEO has improved the global exploration and local development capabilities of the golden eagle optimizer (GEO) algorithm. …”
Get full text

Prediction of Lithium-Ion Battery State of Health Using a Deep Hybrid Kernel Extreme Learning Machine Optimized by the Improved Black-Winged Kite Algorithm by Juncheng Fu, Zhengxiang Song, Jinhao Meng, Chunling Wu

“…Addressing the non-linear and non-stationary characteristics of battery capacity sequences, a novel method for predicting lithium battery SOH is proposed using a deep hybrid kernel extreme learning machine (DHKELM) optimized by the improved black-winged kite algorithm (IBKA). …”
Get full text