An Optimization Model for Production Scheduling in Parallel Machine Systems by Leting Zu, Wenzhu Liao, Xiaoxia Yang

“…A numerical example is presented to illustrate the computational process, accompanied by an extensive discussion of the results showcasing improved performance. Furthermore, the optimization model developed in this paper can be adapted to tackle the production scheduling problem with modifications tailored for parallel machines.…”
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Research on 5G base station energy saving system based on DCNN-LSTM load prediction algorithm by Jianbin WANG, Shuchun WANG, Shangjin LIAO, Shuyuan SHI

“…With the rapid construction of the 5G wireless communication network, the energy consumption pressure of operators, and even the overall communication industry, is simultaneously highlighted.Achieving sustainable development of the industry through energy conservation and consumption reduction has become a new research direction for the current 5G network development.Taking the PRB rate as the load evaluation index, LSTM model was improved by using DCNN to extract the depth feature of the cell’s indicators.A set of DCNN-LSTM deep learning model that could predict the future value of PRB rate was proposed.On the basis of the improved algorithm, the network topology of the current 5G access network was optimized.An additional network element and its working system were designed.An intelligent energy-saving system, which ensured the network experience, of 5G base stations was realized.…”
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Research on trajectory planning method of anchor drilling robot manipulator by ZHANG Jun, LI Wanye, GUO Jiahua, LI Jingkai, HE Xinyue, WU Zhongbin

“…In order to enhance the efficiency of tunnel support in coal mines, a study focused on the six-degree-of-freedom drill anchor robot manipulator arm and proposed an optimal trajectory planning method based on an improved grey wolf optimization algorithm. …”
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REVIEW OF FEATURE SELECTION METHODS USING OPTIMIZATION ALGORITHM (Review paper for optimization algorithm) by Zana O. Hamad

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Weakly supervised semantic segmentation and optimization algorithm based on multi-scale feature model by Changzhen XIONG, Hui ZHI

“…In order to improve the accuracy of weakly-supervised semantic segmentation method,a segmentation and optimization algorithm that combines multi-scale feature was proposed.The new algorithm firstly constructs a multi-scale feature model based on transfer learning algorithm.In addition,a new classifier was introduced for category prediction to reduce the failure of segmentation due to the prediction of target class information errors.Then the designed multi-scale model was fused with the original transfer learning model by different weights to enhance the generalization performance of the model.Finally,the predictions class credibility was added to adjust the credibility of the corresponding class of pixels in the segmentation map,avoiding false positive segmentation regions.The proposed algorithm was tested on the challenging VOC 2012 dataset,the mean intersection-over-union is 58.8% on validation dataset and 57.5% on test dataset.It outperforms the original transfer-learning algorithm by 12.9% and 12.3%.And it performs favorably against other segmentation methods using weakly-supervised information based on category labels as well.…”
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Improvement of Heavy Load Robot Positioning Accuracy by Combining a Model-Based Identification for Geometric Parameters and an Optimized Neural Network for the Compensation of Nong... by Yuxiang Wang, Zhangwei Chen, Hongfei Zu, Xiang Zhang, Chentao Mao, Zhirong Wang

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Resource scheduling algorithm of satellite communication system for future multi-beam dense networking by Yuanzhi HE, Cong PENG, Jihong YU, Yun LIU

“…The resource scheduling problem of satellite communication systems under the condition of high-dynamic and resource limitation was studied.A resource scheduling model for satellite communication systems was established based on time window, energy consumption, number of channels, user priority and task suddenness.Considering the disadvantages of slow initial search speed and weak local search ability, the improved ant colony algorithm based on construction of initial solution set and extra pheromone deposition was proposed to solve the resource scheduling problem.The optimization characteristics of the number of completed tasks, priority and scheduling completion time were simulated and analyzed.The results show that the algorithm has a fast convergence rate.Compared with the same type optimization algorithm, the algorithm has high scheduling efficiency, therefore, it is suitable for scheduling satellite communication system resources for multi-beam dense networking in the future.…”
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Improved Block Element Method for Simulating Rock Failure by Yan Han, Qingwen Ren, Lei Shen, Yajuan Yin

“…To realistically simulate rock damage paths, this work improves the traditional BEM by using random Voronoi polygonal grids for discrete modeling. …”
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Improved faster R-CNN for steel surface defect detection in industrial quality control by Yuefeng Leng, Jiazhi Liu

“…Evaluated on the NEU-DET dataset, the optimized model achieves a mean average precision (mAP) of 80.2%-yielding a 12.6% improvement over the baseline-while increasing detection speed by 40.9%. …”
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An unmanned intelligent inspection technology based on improved reinforcement learning algorithm for power large-area multi-scene inspection by Enmin Wang, Xin Meng, Jinglong Yu, Jiechang Wang, Liang Yin

“…Consequently, this study investigates a multi scene unmanned intelligent patrol technology for power large area, based on an improved reinforcement learning algorithm. The unmanned intelligent patrol model is designed according to the patrol UAVs, wireless charging piles distributed in appropriate locations, and the targets to be patrolled (i.e., multiple scenes within a large power area). …”
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Research on Stacking Distribution of Steel Plates Input Based on Improved Multi-objective Particle Swarm Optimization by ZHONG Chuanjie, CHENG Wenming, DU Run, GAO Xuchao, ZHANG Lin

“…Finally, the stacking situations before and after optimization were compared. Compared to the traditional stacking method used before optimization, the optimized stacking distribution scheme improved by 19.35%, 4.97%, and 62.23% under the three objectives, respectively, indicating a more significant optimization effect.ConclusionsBased on the actual demand of enterprises for optimizing automatic steel plate warehouse loading decisions, the PCDMOPSO algorithm has demonstrated good performance in the simulation test of solving the stack allocation model. …”
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Short-Term Electricity Load Forecasting Based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and Improved Sparrow Search Algorithm–Convolutional Neural Netwo... by Han Qiu, Rong Hu, Jiaqing Chen, Zihao Yuan

“…Accurate power load forecasting plays an important role in smart grid analysis. To improve the accuracy of forecasting through the three-level “decomposition–optimization–prediction” innovation, this study proposes a prediction model that integrates complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), the improved sparrow search algorithm (ISSA), a convolutional neural network (CNN), and bidirectional long short-term memory (BiLSTM). …”
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Improving Modularity Regularization Techniques for Estimating Structures in Complex Network by Samaa F. Ibraheem, Basad Al-Sarray

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Simplifying Multiproject Scheduling Problem Based on Design Structure Matrix and Its Solution by an Improved aiNet Algorithm by Chunhua Ju, Tinggui Chen

“…In this paper, design structure matrix (DSM) and an improved artificial immune network algorithm (aiNet) are developed to solve a multi-mode resource-constrained scheduling problem. …”
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Optimization of Rendering Parameters of Cesium 3DTiles Model Based on Differential Evolution Algorithm by Doujun Zhang, Yong Wu, Youcong Ni, Tinghuang Zhang, Chenxiang Gao

“…In this paper, we proposed a multi-strategy probabilistic discrete differential evolution algorithm (MSPDDE) for finding the optimal values of the rendering parameters of Cesium 3DTiles model, which increases the search space and improves the convergence speed by introducing multiple mutation strategies. …”
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Optimization of New Energy Vehicle Industry Structure Based on Optimization Link Prediction Similarity Algorithm and CGE by Zhenjun Xie

“…In light of the growing global concerns over energy and climate change, new energy vehicles are confronted with both opportunities and challenges posed by industrial structural transformation. To foster the optimization of the new energy vehicle industry structure while considering environmental impact, this paper first uses an improved link prediction algorithm to construct an industrial structure optimization model. …”
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Target image detection algorithm of complex road scene based on improved multi-scale adaptive feature fusion technology by Xu Zhaosheng, Liao Zhongming, Xiao Xiaoyong, Ahmad Suzana, Mat Diah Norizan, Ismail Azlan

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Using multiple machine learning algorithms to optimize the water quality index model and their applicability by Fei Ding, Shilong Hao, Wenjie Zhang, Mingcen Jiang, Liangyao Chen, Haobin Yuan, Nan Wang, Wenpan Li, Xin Xie

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Prediction of Urban Scale Expansion Based on Genetic Algorithm Optimized Neural Network Model by Hewu Kuang

“…The genetic algorithm is improved by immune cloning algorithm, and the CGA-BP neural network model is established to obtain the global optimal solution. …”
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Simulation and Optimization of Automated Guided Vehicle Charging Strategy for U-Shaped Automated Container Terminal Based on Improved Proximal Policy Optimization by Yongsheng Yang, Jianyi Liang, Junkai Feng

“…This paper proposes a simulation-based optimization method for AGV charging strategies in U-shaped ACTs based on an improved Proximal Policy Optimization (PPO) algorithm. …”
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