-
1161
Solar Irradiance Prediction Method for PV Power Supply System of Mobile Sprinkler Machine Using WOA-XGBoost Model
Published 2024-11-01“…Based on meteorological data provided by ten typical radiation stations uniformly distributed nationwide, an Extreme Gradient Boosting (XGBoost) model optimized using the Whale Optimization Algorithm (WOA) is developed to predict solar radiation. …”
Get full text
Article -
1162
Optimizing sustainable blended concrete mixes using deep learning and multi-objective optimization
Published 2025-05-01“…The Multi-Objective Particle Swarm Optimization (MOPSO) algorithm finds multiple optimal solutions which simultaneously optimize three competing objectives that include strength maximization and cost minimization and cement reduction. …”
Get full text
Article -
1163
Facility location problem for senior centers in an upcoming super-aging society
Published 2025-02-01“…This study aims to address the facility location problem for senior centers in upcoming super-aging societies. An optimization model is developed using a genetic algorithm to determine the optimal locations of senior centers. …”
Get full text
Article -
1164
-
1165
Configurational Comparison of a Binary Logic Transmission Unit Applicable to Agricultural Tractor Hydro-Mechanical Continuously Variable Transmissions and Its Wet Clutch Optimizati...
Published 2025-04-01“…Under light-load conditions, the optimized GRNN reduced total relative error by 39.6%, while under heavy-load conditions, it achieved a 61% reduction. …”
Get full text
Article -
1166
Optimal Design for a Novel Compliant XY Platform Integrated with a Hybrid Double Symmetric Amplifier Comprising One-Lever and Scott–Russell Mechanisms Arranged in a Perpendicular S...
Published 2025-07-01“…The pseudo-rigid body model (PRBM), Lagrangian approach, finite element analysis (FEA), and Firefly optimization algorithm were employed to develop, verify, and optimize the quality response of the new positioner. …”
Get full text
Article -
1167
-
1168
Adaptive Bacterial Foraging Optimization
Published 2011-01-01“…Bacterial Foraging Optimization (BFO) is a recently developed nature-inspired optimization algorithm, which is based on the foraging behavior of E. coli bacteria. …”
Get full text
Article -
1169
Congestion Influence on Optimal Bidding in a Competitive Electricity Market using Particle Swarm Optimization
Published 2024-02-01“…In this paper, the bidding strategy problem with congestion management is modeled as an optimization problem and solved using Particle Swarm Optimization (PSO). …”
Get full text
Article -
1170
Application of Genetic Algorithms in Nonlinear Heat Conduction Problems
Published 2014-01-01“…Genetic algorithms are employed to optimize dimensionless temperature in nonlinear heat conduction problems. …”
Get full text
Article -
1171
-
1172
Routing and Scheduling in Time-Sensitive Networking by Evolutionary Algorithms
Published 2025-05-01“…In this paper, we propose a novel routing and scheduling approach for TSN based on evolutionary algorithm. Specifically, we introduce a flow grouping method that leverages the greatest common divisor to optimize flow aggregation. …”
Get full text
Article -
1173
Energy consumption optimization scheme in UAV-assisted MEC system based on optimal SIC order
Published 2024-02-01“…In uplink non-orthogonal multiple access (NOMA)-based unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) system, the successive interference cancellation (SIC) order of NOMA became a bottleneck limiting the transmission performance of task offload in uplink link.To reduce the energy consumption of the system, the SIC order was discussed and the optimal SIC order based on channel gain and task delay constraint was proposed.The optimization problem of minimizing the system energy consumption was proposed based on the optimal SIC order while satisfying the constraints of the given task delay of the device, the maximum transmit power constraint of the device, and the UAV trajectory.Since the problem was a complex non-convex problem, an alternating optimization method was adopted to solve the optimization problem to achieve power allocation and UAV trajectory optimization.A low-complexity algorithm based on matching theory was proposed to obtain the optimal device grouping in different time slots.Simulation results show that the optimal SIC order can realize smaller system energy consumption under the same task delay constraint compared with other SIC order, the proposed low-complexity device grouping algorithm can obtain the optimal device grouping.…”
Get full text
Article -
1174
Energy consumption optimization scheme in UAV-assisted MEC system based on optimal SIC order
Published 2024-02-01“…In uplink non-orthogonal multiple access (NOMA)-based unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) system, the successive interference cancellation (SIC) order of NOMA became a bottleneck limiting the transmission performance of task offload in uplink link.To reduce the energy consumption of the system, the SIC order was discussed and the optimal SIC order based on channel gain and task delay constraint was proposed.The optimization problem of minimizing the system energy consumption was proposed based on the optimal SIC order while satisfying the constraints of the given task delay of the device, the maximum transmit power constraint of the device, and the UAV trajectory.Since the problem was a complex non-convex problem, an alternating optimization method was adopted to solve the optimization problem to achieve power allocation and UAV trajectory optimization.A low-complexity algorithm based on matching theory was proposed to obtain the optimal device grouping in different time slots.Simulation results show that the optimal SIC order can realize smaller system energy consumption under the same task delay constraint compared with other SIC order, the proposed low-complexity device grouping algorithm can obtain the optimal device grouping.…”
Get full text
Article -
1175
Error Covariance Analyses for Celestial Triangulation and Its Optimality: Improved Linear Optimal Sine Triangulation
Published 2025-04-01“…While current methods like Linear Optimal Sine Triangulation (LOST) provide statistically optimal solutions for position estimation using multiple celestial body observations, their performance can be compromised by suboptimal measurement pair selection. …”
Get full text
Article -
1176
DMS Algorithm in the Application of the Map/Reduce Tasks Schedule
Published 2019-02-01“…The whole efficiency of traditional task scheduling algorithms is low under the cloud environment, In order to improve the whole efficiency of the task scheduling, this article based on Map/Reduce presents a Difference Matrix Scheduling tasks schedule algorithm based on processing time. …”
Get full text
Article -
1177
Cost-optimal sizing of battery energy storage systems in microgrids using artificial Rabbits optimization
Published 2025-09-01“…This paper presents a cost-optimal sizing framework for Battery Energy Storage Systems (BESS) in grid-connected microgrids using the Artificial Rabbits Optimization (ARO) algorithm. …”
Get full text
Article -
1178
Multi-Level Particle System Modeling Algorithm with WRF
Published 2025-05-01“…Based on the multi-scale mean-shift clustering algorithm, Adaptive Kernel Density Estimation (AKDE) is introduced to map density to bandwidth, achieving adaptive adjustment of clustering bandwidth while reducing computational resources and improving cloud hierarchy. …”
Get full text
Article -
1179
An intelligent hybrid grey wolf-particle swarm optimizer for optimization in complex engineering design problem
Published 2025-05-01“…To overcome these limitations and enhance solution quality, this study proposes a novel Hybrid Grey Wolf-Particle Swarm Optimization (HGWPSO) algorithm. HGWPSO integrates the exploration ability of GWO with the rapid convergence and exploitation efficiency of PSO. …”
Get full text
Article -
1180
Feature engineering through two-level genetic algorithm
Published 2025-09-01“…This study highlights the utility of evolutionary algorithms to generate feature sets that enhance the performance of interpretable machine learning models.…”
Get full text
Article