Development of Model for Traffic Flows on Urban Street and Road Network by D. V. Kapskiy, D. V. Navoy, P. A. Pegin

“…The developed model has a complex structure of algorithmic support. …”
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Design of an Efficient Deep Learning-Based Diagnostic Model for Wind Turbine Gearboxes Using SCADA Data by Xuan-Kien Mai, Jun-Yeop Lee, Jae-In Lee, Byeong-Soo Go, Seok-Ju Lee, Minh-Chau Dinh

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Production Dynamic of Coal-bed Methane After Well Pressure Based on Multi-layer Perceptron Model Inversion Study by LI Jingsong, WANG Tao, WANG Jinwei, WEI Zhipeng, XIAO Cong, TANG Jizhou

“…The inversion of production performance after fracturing of coal-bed methane well is the key technology to realize the efficient development of gas reservoir. In order to improve the inversion efficiency of traditional numerical simulation methods, with the help of machine learning modeling technology and intelligent algorithm, this paper studies the automatic inversion and programmed design of key parameters such as coal-bed methane reservoir matrix permeability, gas saturation, fracture half length, fracture number and fracture conductivity. …”
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Modeling of Cloud-Edge Collaborated Electricity Market Considering Flexible Ramping Products Provided by VPPs by PENG Chaoyi, CHEN Wenzhe, XU Suyue, LI Jianshe, ZHOU Huafeng, GU Huijie, NIE Yongquan, SUN Haishun

“…The distributed optimization model is iteratively solved using the analytical target cascading (ATC) method, and heuristic constraints are introduced to improve the convergence of the algorithm. …”
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Time-Variation Damping Dynamic Modeling and Updating for Cantilever Beams with Double Clearance Based on Experimental Identification by Yunhe Zhang, Fanjun Meng, Xueguang Li, Wei Song, Dashun Zhang, Faping Zhang

“…The accuracy of a space manipulator’s end trajectory and stability is significantly affected by joint clearance. Aiming to improve the prediction accuracy of vibration caused by clearance, a dynamic clearance modeling method is developed based on parameter identification in this study. …”
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Modeling of cross line operation of urban rail transit trains based on passenger travel time by LUO Qin, LIN Bin, GU Mengqi, YANG Liang, ZHANG Xiaochun

“…The model is solved by genetic algorithm. The scheme of metro Line Ⅰ of city S crossing into Line Ⅱ is used as an example to verify the feasibility of the model, and the optimal train density under different train load rates is obtained. …”
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Robust beamforming based on the worst-case performance optimization with positive semi-definite constraints by Ding-jie XU, Rui HE, Feng SHEN

“…For the robust adaptive beamforming problem of the gen l signal models, a robust beamforming algorithm based on the worst-case performance optimization with positive semi-definite constraints was proposed. …”
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PERFORMANCE PREDICTION OF ROADHEADERS USING SUPPORT VECTOR MACHINE (SVM), FIREFLY ALGORITHM (FA) AND BAT ALGORITHM (BA) by Arash Ebrahimabadi, Alireza Afradi

“…By understanding the various factors that influence performance, implementing predictive models, and continuously improving machine design and operational strategies, the potential of roadheaders can be maximized. …”
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A novel approach for efficient resource allocation in 6G V2V networks using neighbor-aware greedy algorithm and sweep line model by Spandana Mande, Nandhakumar Ramachandran

“…The resource distribution strategy for V2V users participating in the exchange of information is based on the greedy method. The recommended algorithm determines which resource is optimal for each V2V user by taking a multi-level approach. …”
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Adaptive Grasp Pose Optimization for Robotic Arms Using Low-Cost Depth Sensors in Complex Environments by Aiguo Chen, Xuanfeng Li, Kerui Cen, Chitin Hon

“…Unlike traditional deep learning methods, which suffer from high data dependency and inefficiency with low-precision point clouds, the proposed approach uses ellipsoidal modeling to overcome these issues. The algorithm segments the target and then applies a three-stage optimization to refine the grasping path. …”
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Improving Vehicle Dynamics: A Fractional-Order PI<i>^λ</i>D<i>^μ</i> Control Approach to Active Suspension Systems by Zongjun Yin, Chenyang Cui, Ru Wang, Rong Su, Xuegang Ma

“…A fractional-order PI<i>^λ</i>D<i>^μ</i> (FOPID) controller was proposed, and its structural parameters were optimized using a gray wolf optimization algorithm. …”
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A hybrid bio-inspired augmented with hyper-parameter deep learning model for brain tumor classification by Morolake Oladayo Lawrence

“…To further improve the performance of the model, SSA was increased to select relevant features. …”
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Process Optimization for Complex Product Assembly Workshops with AGV Integration via Discrete Event Simulation by Hailong Song, Shengluo Yang, Shuoxin Yin, Zhigang Xu

“…This model simulates the coordination between AGVs and workstations while optimizing workstation layout and material flow. …”
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Research on Real-Time Control Strategy of Air-Conditioning Water System Based on Model Predictive Control by Dehan Liu, Jing Zhao, Yibing Wu, Zhe Tian

“…Compared with the day-ahead MPC algorithm, the temperature following control accuracy can be relatively improved by 16.52%, and the cooling capacity can be saved by 1.24%.…”
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Maintaining rockfall protection in mountain forests under climate change: optimizing management for sustainable stem size distributions by Ulrike Hiltner, Jonas Glatthorn, Timothy Thrippleton, Harald Bugmann

“…This study uses a simulation-based optimization approach, integrating the dynamic forest model ForClim with the Simulated Annealing optimization algorithm, to identify adaptive management strategies for Swiss forests. …”
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Method on intrusion detection for industrial internet based on light gradient boosting machine by Xiangdong HU, Lingling TANG

“…Intrusion detection is a critical security protection technology in the industrial internet, and it plays a vital role in ensuring the security of the system.In order to meet the requirements of high accuracy and high real-time intrusion detection in industrial internet, an industrial internet intrusion detection method based on light gradient boosting machine optimization was proposed.To address the problem of low detection accuracy caused by difficult-to-classify samples in industrial internet business data, the original loss function of the light gradient boosting machine as a focal loss function was improved.This function can dynamically adjust the loss value and weight of different types of data samples during the training process, reducing the weight of easy-to-classify samples to improve detection accuracy for difficult-to-classify samples.Then a fruit fly optimization algorithm was used to select the optimal parameter combination of the model for the problem that the light gradient boosting machine has many parameters and has great influence on the detection accuracy, detection time and fitting degree of the model.Finally, the optimal parameter combination of the model was obtained and verified on the gas pipeline dataset provided by Mississippi State University, then the effectiveness of the proposed mode was further verified on the water dataset.The experimental results show that the proposed method achieves higher detection accuracy and lower detection time than the comparison model.The detection accuracy of the proposed method on the gas pipeline dataset is at least 3.14% higher than that of the comparison model.The detection time is 0.35s and 19.53s lower than that of the random forest and support vector machine in the comparison model, and 0.06s and 0.02s higher than that of the decision tree and extreme gradient boosting machine, respectively.The proposed method also achieved good detection results on the water dataset.Therefore, the proposed method can effectively identify attack data samples in industrial internet business data and improve the practicality and efficiency of intrusion detection in the industrial internet.…”
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A Deformation Prediction Model for Concrete Dams Based on RSA-VMD-AttLSTM by Pei Liu, Hao Gu, Chongshi Gu, Yanbo Wang

“…Analysis of the five evaluation criteria revealed that the RSA can better optimize the parameters of the VMD algorithm. Consequently, the proposed model demonstrates superior noise reduction capabilities and improved prediction accuracy.…”
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HAMF: A Novel Hierarchical Attention-Based Multi-Modal Fusion Model for Parkinson&#x2019;s Disease Classification and Severity Prediction by Anitha Rani Palakayala, P. Kuppusamy, D. Kothandaraman, Gunakala Archana, Jaideep Gera

“…This leads to richer feature extraction, besides fusing different data modalities with accurate integration. Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) methods are used in optimizing the model, by which the convergence speed raised by 15&#x2013;20 %. …”
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Research on the Capability Maturity Evaluation of Intelligent Manufacturing Based on Firefly Algorithm, Sparrow Search Algorithm, and BP Neural Network by Li Shi, Xuehong Ding, Min Li, Yuan Liu

“…In order to overcome the shortcoming of SSA that it is easy to fall into the local optimum, the firefly disturbance strategy is introduced to improve it, a new sparrow search algorithm (FASSA) is proposed, and on this basis, an intelligent manufacturing capability maturity evaluation model based on the FASSA-BP algorithm is constructed. …”
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A Hybrid Security Framework for Train-to-Ground (T2G) Communication Using DOA-Optimized BPNN Detection, Bayesian Risk Scoring, and RL-Based Response by Chaoyuan Sun, Weijiao Zhang, Peng Sun, Hui Wang, Chunhui Yang

“…First, feature selection is performed on the TON_IoT dataset to develop a Dream Optimization Algorithm (DOA)-optimized backpropagation neural network (DOA-BPNN) model for efficient anomaly detection. …”
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