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Comprehensive Evaluation Method of Teaching Effect Based on Particle Swarm Optimization Neural Network Model
Published 2022-01-01“…In view of these characteristics, this paper has conducted in-depth research to fully prove the feasibility and superiority of the content of this article. The specific summary is as follows: (1) Introduced the design concept of particle swarm optimization teaching evaluation system. (2) The use of object-oriented programming algorithms makes it easier for the algorithm to find an entry point, solve practical problems, and optimize the reusability of the algorithm method. (3) Particle swarm optimization based on quantum behavior, adjusting parameter values, the highest and the lowest, greatly reduces the difficulty of program parameter adjustment. (4) In terms of operation, it can quickly and efficiently complete the maintenance of teacher teaching information, evaluation relationship management of teacher teaching quality evaluation, evaluation content management, student evaluation, supervision evaluation, college leadership evaluation, evaluation performance management, and other operations. …”
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582
Size optimization method of the Watt-II six-bar mechanism based on particle swarm optimization
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Next-Gen Connectivity: Exploring UAV Swarm Applications in Cell-Free Massive MIMO for IIoT
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586
Adaptive Traffic Lights Control System Using Deep Q-Network and Salp Swarm Optimization
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Democratization of Crop Irrigation: A Socio-Technical Optimization Approach Using Particle Swarm Optimization
Published 2025-07-01“…To do this, we propose a collective irrigation system using a Particle Swarm Optimization (PSO) algorithm, to accurately estimate crop water needs, a method of equitable distribution of water according to needs. …”
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590
Control and Stability Analysis of Double Time-Delay Active Suspension Based on Particle Swarm Optimization
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Research on Energy-Saving Optimization Control Strategy for Distributed Hub Motor-Driven Vehicles
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593
A Review of Research on Path Planning of Unmanned Surface Vessel Swarm: Deep Reinforcement Learning
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594
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Redefining IoT networks for improving energy and memory efficiency through compressive sensing paradigm
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Optimization Design of Node Placement Manipulators Based on Working Area and Response Speed
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Optimizing capacitor size and placement in radial distribution networks for maximum efficiency
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598
3D Deployment Optimization of Wireless Sensor Networks for Heterogeneous Functional Nodes
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Application of Three Neural Network Models in the Prediction ofStratospheric Wind Field
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Low-carbon optimization planning method for integrated energy system based on DG uncertainty affine model
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