Optimization of TCN-BiLSTM for dissolved oxygen prediction based on improved sparrow search algorithm by Pei Shi, Mingjie Tang, Quan Wang, Xiaofei Ma

“…To address these challenges, this paper proposes a dissolved oxygen prediction method based on an improved sparrow search algorithm optimized TCN- BiLSTM (SMI-TCN BiLSTM). …”
Get full text

Optimizing the Joint Replenishment and Channel Coordination Problem under Supply Chain Environment Using a Simple and Effective Differential Evolution Algorithm by Lin Wang, Hui Qu, Shan Liu, Can Chen

Get full text

Enhanced probabilistic prediction of pavement deterioration using Bayesian neural networks and cuckoo search optimization by Feng Xiao, Biying Shi, Jie Gao, Huapeng Chen, Di Yang

“…Therefore, this study proposed an improved probabilistic model for pavement deterioration prediction based on the coupling of Bayesian neural network (BNN) and cuckoo search (CS) algorithm. …”
Get full text

Optimization of integrated energy system considering P2G oxygen-enriched improvement and hybrid solar energy utilization by Xiaohui YANG, Zhao WAN, Riying XIAO, Zeyu YANG, Zecheng HU, Chilyu WU

“…The simulation results show that the CO2 emissions are reduced by 75.83% compared to the oxygen-enriched improvement before, and the total solar energy output is increased by 9.79% compared to the scenario without combined solar energy, indicating that the proposed model can effectively reduce carbon emissions and operating costs.…”
Get full text

Utilization of Machine-Learning-Based model Hybridized with Meta-Heuristic Frameworks for estimation of Unconfined Compressive Strength by She Wang, Qi Zhang

“…The current study considers the RBF-based machine learning model, whose parameters have been optimized using two enhanced metaheuristic frameworks: Improved Arithmetic Optimization Algorithm (IAOA) and Flying Foxes Optimization (FFO). …”
Get full text

A Deep Reinforcement Learning-Driven Seagull Optimization Algorithm for Solving Multi-UAV Task Allocation Problem in Plateau Ecological Restoration by Lijing Qin, Zhao Zhou, Huan Liu, Zhengang Yan, Yongqiang Dai

“…The algorithm improves both global and local search capabilities by optimizing key phases of seagull migration, attack, and post-attack refinement. …”
Get full text

A solution to the Single-School school bus routing problem considering accessibility and economy by Zizhan Jiang, Jiying Wang, Siyuan Huang, Hua Daniel Xu

“…A well-designed SBRP strategy can reduce the operating costs of the school bus system, improve accessibility, and ensure timely arrival for teachers and students. …”
Get full text

Hybridization of deep learning models with crested porcupine optimizer algorithm-based cybersecurity detection on industrial IoT for smart city environments by Sarah A. Alzakari, Mohammed Aljebreen, Mashael M. Asiri, Wahida MANSOURI, Sultan Alahmari, Mohammed Alqahtani, Shaymaa Sorour, Wafi Bedewi

“…This study presents Cybersecurity using a Crested Porcupine Optimizer Algorithm with Hybrid Deep Learning Models (CCPOA-HDLM). …”
Get full text

Advanced Vehicle Routing for Electric Fleets Using DPCGA: Addressing Charging and Traffic Constraints by Yuehan Zheng, Hao Chang, Peng Yu, Taofeng Ye, Ying Wang

“…With the rapid proliferation of electric vehicles (EVs), urban logistics faces increasing challenges in optimizing vehicle routing. This paper presents a new modeling framework for the Electric Vehicle Routing Problem (EVRP), where multiple electric trucks serve a set of customers within their capacity limits. …”
Get full text

Mathematical Models for Management Information Systems on Digital Platforms: from Resource Management to Demand Forecasting by Viktor Godliuk

“…The use of optimization methods, graph algorithms, forecasting, and machine learning to improve the efficiency of digital systems is investigated. …”
Get full text

LM-CNN-based Automatic Cost Calculation Model for Power Transmission and Transformation Projects by Xiaolin WU, Ling LUAN, Lianwu PAN, Hailong LI

“…Compared with the BP neural network and GD-CNN, the proposed model with higher prediction accuracy and stability combines the advantages of Levenberg-Marquart algorithm and convolutional neural network model to improve the calculation effect of power transmission and transformation project cost.…”
Get full text

Ensemble machine learning algorithm for cost-effective and timely detection of diabetes in Maiduguri, Borno State by Emmanuel Gbenga Dada, Aishatu Ibrahim Birma, Abdulkarim Abbas Gora

“…The proposed WAEL model ingeniously combines five feature spaces through the grey wolf optimisation (GWO) algorithm to uncover the optimal weight combination. …”
Get full text

Improvements of particle filter optimization algorithm for robust optimization under different types of uncertainties by Éva Kenyeres, Alex Kummer, János Abonyi

“…This paper presents a widely usable sampling-based methodology by improving the Particle Filter Optimization (PFO) algorithm. …”
Get full text

Prediction of cardiovascular disease based on multiple feature selection and improved PSO-XGBoost model by Kerang Cao, Chang Liu, Siqi Yang, Yuxin Zhang, Lili Li, Hoekyung Jung, Shuo Zhang

“…In order to predict it more accurately, this paper proposes a cardiovascular disease prediction model that combines multiple feature selection, improved particle swarm optimization algorithm, and extreme gradient boosting tree. …”
Get full text

Mathematical modelling and optimization of cutting conditions in turning operation on MDN 350 steel with carbide inserts by Syed Adil, A. Krishnaiah, D. Srinivas Rao

“…Genetic Algorithm, which is an advanced optimization technique known for its intricate search for optimal solutions, is used for optimizing surface roughness with optimal combination of the geometrical parameters. …”
Get full text

Optimization on Electric Construction Machinery Considering Time‐of‐Use Electricity Price Based on the Improved Crested Porcupine Optimizer Algorithm by Dawei Wang, Bo Gao, Lei Zhang

“…This paper introduces an innovative algorithm, the improved crested porcupine optimizer (ICPO), which incorporates Latin hypercube sampling for population initialization. …”
Get full text

Online Vulnerability Assessment in Cascading Failure Analysis Using an Intelligence Monitoring Model by Saber Armaghani, Zahra Moravej

“…Thus, in this paper, Demand Response modeling will be based on determining the cost of electric energy consumption in the emergency of the network in such a way as to cause a shift of consumption to improve the performance of the network. …”
Get full text

Framework for truck–RPAS hybrid models in last-mile delivery by Armin Mahmoodi, Leila Hashemi, Jeremy Laliberte

“…High-quality Pareto-optimal solutions are produced by the non-dominated sorting genetic algorithm II, which methodically manages trade-offs between the conflicting goals. …”
Get full text

FedDBO: A Novel Federated Learning Approach for Communication Cost and Data Heterogeneity Using Dung Beetle Optimizer by Dongyan Wang, Limin Chen, Xiaotong Lu, Yidi Wang, Yue Shen, Jingjing Xu

“…This paper proposes a federated learning approach based on the dung beetle optimizer, named FedDBO. In this method, the model parameters uploaded from clients to the server are transformed into model scores. …”
Get full text

Multi-Target Firefighting Task Planning Strategy for Multiple UAVs Under Dynamic Forest Fire Environment by Pei Zhu, Shize Jiang, Jiangao Zhang, Ziheng Xu, Zhi Sun, Quan Shao

“…In this process, the study considers only the use of fire-extinguishing balls as the fire suppressant for the UAVs. The improved multi-population grey wolf optimization (MP–GWO) algorithm and non-Dominated sorting genetic algorithm II (NSGA-II) were designed to solve the path planning and task allocation models, respectively. …”
Get full text