Movie Box Office Prediction Based on IFOA-GRNN by Wei Lu, Xiaoqiao Zhang, Xinchen Zhan

“…The contribution of this article is to propose a generalized regression neural network model based on an improved fruit fly optimization algorithm, which can greatly improve the accuracy of movie box office prediction.…”
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Constrained total least squares localization using angle of arrival and time difference of arrival measurements in the presence of synchronization clock bias and sensor position er... by Ruirui Liu, Ding Wang, Jiexin Yin, Ying Wu

“…Based on measurements of angle of arrival and time difference of arrival, a method is proposed to improve the accuracy of localization with imperfect sensors. …”
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Orchard Navigation Method Based on RS-SC Loop Frame Search Method and SLAM Technology by Ning Xu, Qingshan Meng, Fengping Liu, Zhihe Li, Guangming Wang, Na Guo, Wenxuan Wu

“…In the loop frame matching, an optimization algorithm combining normal distribution transformation and iterative nearest point is used to reduce the cumulative error significantly. …”
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Broad learning system based on attention mechanism and tracking differentiator by LIAO Lüchao, ZOU Weidong, YANG Jialong, LU Huihuang, XIA Yuanqing, GAO Jianlei

“…In terms of model structure, A-TD-BLS introduced self-attention mechanism to the original BLS, and further fused and transformed the extracted features through attention weighting to improve the feature learning ability.In terms of model training methods, a weight optimization algorithm based on tracking differentiator was designed.This method effectively alleviates the overfitting phenomenon of the original BLS by limiting the size of the weight values, significantly reduces the influence of the number of hidden layer nodes on model performance and makes the generalization performance more stable.Moreover, the training algorithm was extended to the BLS incremental learning framework, so that the model can improve performance by dynamically adding hidden layer nodes.Multiple experiments conducted on some benchmark datasets show that compared to the original BLS, the classification accuracy of A-TD-BLS is increased by 1.27% on average on classification datasets and the root mean square error of A-TD-BLS is reduced by 0.53 on average on regression datasets.Besides, A-TD-BLS is less affected by the number of hidden layer nodes and has more stable generalization performance. …”
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Research on Short-Term Load Forecasting of LSTM Regional Power Grid Based on Multi-Source Parameter Coupling by Bo Li, Yaohua Liao, Siyang Liu, Chao Liu, Zhensheng Wu

“…In order to further optimize the performance of the LSTM model, the IPSO algorithm, and linear difference decreasing inertia weight are introduced to improve the global optimization ability and convergence speed of the PSO algorithm and reduce the risk of local optimal solutions. …”
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Reinforcement Learning for Computational Guidance of Launch Vehicle Upper Stage by Shiyao Li, Yushen Yan, Hao Qiao, Xin Guan, Xinguo Li

“…This manuscript investigates the use of a reinforcement learning method for the guidance of launch vehicles and a computational guidance algorithm based on a deep neural network (DNN). Computational guidance algorithms can deal with emergencies during flight and improve the success rate of missions, and most of the current computational guidance algorithms are based on optimal control, whose calculation efficiency cannot be guaranteed. …”
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A multi-dimensional data-driven ship roll prediction model based on VMD-PCA and IDBO-TCN-BiGRU-Attention by Huifeng Wang, Jianchuan Yin, Jianchuan Yin, Nini Wang, Lijun Wang, Lijun Wang

“…Finally,the improved dung beetle optimization (IDBO) algorithm is used to optimize the hyper-parameters of the model. …”
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Optimum Design Research on the Link Mechanism of the JP72 Lifting Jet Fire Truck Boom System by Guo Tong, Wang Jiawen, Liang Yingnan, Peng Buyu, Liu Tao, Liu Yiqun

“…The fmincon function was used to realize the sequential quadratic programming (SQP) algorithm, which is one of the most effective methods to solve the constrained nonlinear optimization problems, for the optimal design. …”
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Selection Based on Colony Fitness for Differential Evolution by Zi Ming, Yang Li, Shijie Peng, Xuechao Wu, Jinyi Guo

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A Short-Term Load Forecasting Method Considering Multiple Factors Based on VAR and CEEMDAN-CNN-BILSTM by Bao Wang, Li Wang, Yanru Ma, Dengshan Hou, Wenwu Sun, Shenghu Li

“…Finally, the sine–cosine and Cauchy mutation sparrow search algorithm (SCSSA) is used to optimize the parameters of the combinative model to improve the forecasting accuracy. …”
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Spatio‐temporal dynamic navigation for electric vehicle charging using deep reinforcement learning by Ali Can Erüst, Fatma Yıldız Taşcıkaraoğlu

“…A recently proposed on‐policy actor–critic method, phasic policy gradient (PPG) which extends the proximal policy optimization algorithm with an auxiliary optimization phase to improve training by distilling features from the critic to the actor network, is used to make EVCS decisions on the network where EV travels through the optimal path from origin node to EVCS by considering dynamic traffic conditions, unit value of EV owner and time‐of‐use charging price. …”
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Enhancing 4G/LTE Network Path Loss Prediction with PSO-GWO Hybrid Approach by Messaoud Garah, Nabil Boukhennoufa

“…Furthermore, a hybrid optimization model, PSO-GWO, is proposed to improve prediction accuracy. …”
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Multidisciplinary Collaborative Reliability Analysis of the Gear Reducer based on Inverse Reliability Strategy by Wang Liangliang, Peng Jinshuan, Shao Yiming

“…The IRS- GA- CO,which not only lifted the coupling between all disciplines to improve the search most probable point,the burden of system- level optimizer also can be significantly reduced. …”
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Performance evaluation of an adopted model based on big-bang big-crunch and artificial neural network for cloud applications by Pradeep Rawat, Robin Singh Bhadoria, Punit Gupta, Priti Dimri, G. P. Saroha

“…The proposed model is inspired from Big-Bang Big-Crunch algorithm in astrology. The work has been compared with a genetic algorithm, Particle swarm optimization and TOPSIS algorithm. …”
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State of Health Estimation of Lithium-Ion Batteries Using Fusion Health Indicator by PSO-ELM Model by Jun Chen, Yan Liu, Jun Yong, Cheng Yang, Liqin Yan, Yanping Zheng

“…This optimization enhances the ELM’s performance, addressing instability issues in the standard algorithm. …”
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A Novel Smart Molecular Fuzzy Decision Support System for Solid-State Battery Investments in Grid-Level Renewable Energy Storage by Gang Kou, Hasan Dincer, Serhat Yuksel, Edanur Ergun, Serkan Eti

“…It is very necessary to determine the most critical indicators to improve the performance of solid-state battery investments. …”
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Cost-efficient dynamic quota-controlled routing in multi-community delay-tolerant networks by Jiagao Wu, Yue Ma, Linfeng Liu

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Time-Dependent Electric Vehicle Routing Problem with Time Windows and Path Flexibility by Li Wang, Shuai Gao, Kai Wang, Tong Li, Lin Li, Zhiyuan Chen

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An integrated approach of feature selection and machine learning for early detection of breast cancer by Jing Zhu, Zhenhang Zhao, Bangzheng Yin, Canpeng Wu, Chan Yin, Rong Chen, Youde Ding

“…Feature selection using recommended algorithm and optimization of the LightGBM model through PSO can significantly enhance the accuracy of breast cancer prediction. …”
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ACO-Based Neural Network to Enhance the Efficiency of Network Controllability of Temporal Networks by Jie Zhang, Ling Ding, Peyman Arebi

“…In the proposed method, a population method based on the ant colony optimization (ACO) algorithm is proposed, which is compatible with temporal networks. …”
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