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Beam Local Stress Prediction Model for Incremental Launching Construction Based on ssa-SVR algorithm

APPLIED SCIENCES-BASEL 2024年第21期14卷 9645页

作者： Ji, Jinke Yang, Runsheng Guo, Hao Li, Qingfu Henan Transportat Investment Grp Jiaozheng Express Zhengzhou 450001 Peoples R China Zhengzhou Univ Sch Water Conservancy & Transportat Zhengzhou 450001 Peoples R China

In the multi-point incremental launching construction process, without setting temporary piers at the mid-span, it is difficult to ensure the synchronization of the launching equipment at the same pier, which can easily cause the beam to deviate from the design axis, leading to changes in the stress of the beam. Calculating the local maximum stress of the beam when lateral deviation occurs is beneficial for establishing a reasonable and reliable threshold for controlling beam deviations. To address this issue, this paper utilizes a finite element model of the bridge under typical adverse conditions, simulating the lateral deviation and asynchronous jacking of the beam to explore stress variation patterns. The results show that the beam stress increases as the lateral deviation and jacking differences increase, severely affecting the structural safety. To overcome the inefficiency of the finite element modeling method when dealing with multiple working conditions and to establish a reasonable deviation control threshold, this study proposes a beam local stress prediction model under the combined influence of lateral deviation and jacking height differences based on the ssa-SVR algorithm. The model calculates the local maximum stress of the beam for 2500 sets of parameters. An engineering case analysis shows that the prediction model has high calculation accuracy, reliable results, fast computational speed, and high efficiency. Based on the stress prediction results, it is recommended to set the jacking height difference control threshold at 20 mm. When the jacking height difference is less than 20 mm, the local maximum stress value under the combined influence of both parameters should be less than the standard limit. The corresponding lateral deviation control threshold can be dynamically adjusted according to the actual travel difference recorded by the jacking equipment, with the control precision improved to 1 mm.

关键词： incremental launching construction ssa algorithm SVR algorithm stress prediction synchronization control of incremental launching construction

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ssa-CNN-LSTM Fusion of Multi-Source Heterogeneous Data for Order Performance Evaluation

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TEHNICKI VJESNIK-TECHNICAL GAZETTE 2025年第2期32卷 576-584页

作者： Qiang, Wei Fang, Yihan Northwestern Polytech Univ Sch Comp CN 127 Youyi West Rd Xian Peoples R China Beijing Inst Printing & Technol CN Sch Mech & Elect Engn 1Sect 2Xinghua St Beijing Peoples R China

With the continuous development of the flexible supply chain in the manufacturing industry of the Industrial Internet of Things and the widespread promotion of the order-oriented production mode, the quantity and types of data involved in order performance evaluation tasks are constantly increasing. The applicability of traditional evaluation methods is significantly weakened, leading to additional investment of manpower and time resources. In response to this issue, this paper proposes a ssa-CNNLSTM multi-source heterogeneous data fusion model aimed at achieving precise order performance evaluation. By integrating and learning data of different structures from various sources, the model fully explores the correlation of data features to obtain precise fusion results, thereby enabling the evaluation of order performance. Simulation experiments conducted on a dataset from a certain intelligent collection customization company demonstrate that the RMSE, MAE, and MAPE of the ssa-CNN-LSTM model results are reduced by 58.71%, 62.94%, and 63.29% respectively compared to the LSTM model, validating the superior accuracy of the proposed model. It also indicates that the model proposed in this study provides new ideas and methods for completing performance evaluation tasks, offering reliable basis and reference for enterprise decision-making, and enriching the research content of the deep learning multi-source heterogeneous data fusion field.

关键词： CNN neural network LSTM neural network multi-source heterogeneous data fusion ssa algorithm

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Classifying walking pattern on different surfaces by optimising features extracted through IMU sensor data using ssa optimisation

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JOURNAL OF THE BRAZILIAN SOCIETY OF MECHANICAL SCIENCES AND ENGINEERING 2025年第1期47卷 1-17页

作者： Chauhan, Preeti Singh, Amit Kumar Raghuwanshi, Naresh K. MNIT Dept Mech Engn Jaipur 302017 India NIT Dept Mech Engn Calicut 673601 India

It is difficult for patients with lower limb amputees to adjust while walking on diverse surfaces as they are fitted with prosthetic feet. It increases their chances of falling and can even result in further injuries. Various researchers are working on developing intelligent feet that can adapt to diverse surfaces. To implement this strategy, it is required to classify walking patterns based on different surfaces. In this study, nine different walking surfaces are selected for classification. Different statistical features and convolution features are extracted from vibration and gyroscopic signals acquired through the IMU sensor attached to the person's body to select the best feature when they are walking on these surfaces. Afterwards, three shallow classifiers, namely SVM, ANN and LightGBM, are trained on these features for classifying these walking patterns on different surfaces. The LightGBM outperforms other shallow classifiers with a maximum accuracy 99.47% for convolutional features. Furthermore, the salp swarm algorithm (ssa) effectively reduces the feature dimension up to 49-56% maintaining the accuracy greater than 99%. Thus, the proposed data-driven methodology effectively classifies walking surfaces using the IMU sensor's data.

关键词： Convolution features LightGBM IMU sensor ssa algorithm Feature selection

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Designing and application of modified ssa based ADRC controller for overhead crane systems

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INTERNATIONAL JOURNAL OF INTELLIGENT ROBOTICS AND APPLICATIONS 2022年第3期6卷 449-466页

作者： Sun, Zhe Zhou, Jichao Ling, Yawen Xie, Xiangpeng Yu, Yunfeng Sun, Zhixin Nanjing Univ Posts & Telecommun Post Ind Technol Res & Dev Ctr State Posts Bur In Post Big Data Technol & Applicat Engn Res Ctr Jia Nanjing 210023 Peoples R China Guoji Beisheng Nanjing Technol Dev Co LTD Nanjing 201705 Peoples R China

In this paper, a modified salp swarm algorithm (ssa) based active disturbance rejection control (ADRC) controller is designed to improve anti-interference and anti-sway control performance for overhead crane systems. Aiming at the ADRC parameter setting problem, the modified ssa is introduced with several methods including the parameter adjustment scheme, adaptive evaluation mobile strategy, opposition-based learning (OBL) strategy and disengagement strategy. By implementing numeric experiment tests, the effectiveness of the modified ssa is confirmed by benchmark functions. Finally, by implementing the simulation experiments under different conditions, the results show that the modified ssa algorithm based ADRC controller has significantly improved the suppression of load swing and position control as well as the anti-interference.

关键词： Overhead crane Anti-swing control ADRC ssa algorithm

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Sea state from ocean video with singular spectrum analysis and extended Kalman filter

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SIGNAL IMAGE AND VIDEO PROCESSING 2022年第6期16卷 1497-1504页

作者： Loizou, Antonis Christmas, Jacqueline Univ Exeter Coll Engn Math & Phys Sci Dept Comp Sci Streatham CampusRennes Dr Exeter EX4 4RN Devon England

A method for estimating key parameters of ocean waves (the dominant frequency and the significant wave height) from uncalibrated monoscopic video is proposed, based on temporal variation of the wave field, specifically time series of pixel intensities. The methodology tracks the principal component of the movement of water in the video, which we propose is associated with the dominant frequency of the ocean. To accomplish this, the singular spectrum analysis algorithm and the extended Kalman filter are used. Then, the shape of an empirical spectrum is used in order to translate the dominant frequency output into a significant wave height estimation.

关键词： Ocean video Sea state ssa algorithm

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MEMS Gyroscope Temperature Compensation Based on ssa-RBF Neural Network 22

MEMS Gyroscope Temperature Compensation Based on SSA-RBF Neu...

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Proceedings of the 2022 5th International Conference on Artificial Intelligence and Pattern Recognition

作者： Yuanhua Liu Ziwei Wang Xinliang Niu School of Telecommunication and Information Engineering & School of Artificial Intelligence Xi'an University of Posts and Telecommunications China Xi'an Branch of China Academy of Space Technology China

ISBN: (纸本)9781450396899

The output of the Micro Electro-mechanical System (MEMS) gyroscope is susceptible affected by temperature drift, which reduces the measurement accuracy of the gyroscope. In this paper, a gyroscope temperature compensation method based on sparrow search algorithm (ssa) and radial basis function (RBF) neural network is proposed to reduce the temperature drift error of gyroscope. Firstly, we utilize the RBF neural network to establish the model of temperature error on the original output of gyroscope; then ssa is employed to find the optimal parameters of the RBF neural network in order to improve its search speed and generalization performance; finally, the optimized RBF neural network is applied to the temperature compensation of the gyroscope. The numerical simulation and comparison results under different temperatures demonstrate that, compared with polynomial and RBF neural network, the ssa-RBF neural network compensation method has superior compensation accuracy and faster convergence speed, which significantly reduces the maximum error, mean value and the standard deviation of gyroscope. Thus, the proposed ssa-RBF method can obtain more accurate fitting performance, effectively compensate the temperature error of MEMS gyroscope, and improve the MEMS gyroscope measurement accuracy.

关键词： MEMS gyroscope RBF neural network ssa algorithm Temperature compensation

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Research on autonomous decision-making technology for once-through steam generator

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ANNALS OF NUCLEAR ENERGY 2023年第1期193卷

作者： Yu, Ren Li, Cheng Yu, Wenmin Song, Xiaosen Wang, Tianshu Naval Univ Engn Wuhan 430033 Peoples R China

In this paper, the innovative research of the autonomous control system of the once-through steam generator (OTSG) is carried out, which is mainly aimed at the normal operating condition, especially the fault condition when the operating characteristics of the system change dramatically. The autonomous control system includes fault diagnosis, autonomous decision-making, hybrid control modules. The Issa algorithm is applied in the research of autonomous decision-making modules because of its strong ability of optimization and fast convergence. This paper improves the ssa algorithm from two aspects: population initialization and finder position update and the optimization ability. The simulation results show that the autonomous control system proposed in this paper can make a decision in the shortest possible time, and provide an effective automatic control method to make the OTSG quickly and smoothly reach the safe state.

关键词： Once -through steam generator Autonomous decision -making ssa algorithm Issa algorithm

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Flood Control Optimization of Reservoir Group Based on Improved Sparrow algorithm (Issa)

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WATER 2023年第1期15卷 132-132页

作者： He, Ji Liu, Sheng-Ming Chen, Hai-Tao Wang, Song-Lin Guo, Xiao-Qi Wan, Yu-Rong North China Univ Water Resources & Elect Power Sch Water Resources Zhengzhou 450011 Peoples R China

The optimal control problem of reservoir group flood control is a complex, nonlinear, high-dimensional, multi-peak extremum problem with many complex constraints and interdependent decision variables. The traditional algorithm is slow and easily falls into the local optimum when solving the problem of the flood control optimization of reservoir groups. The intelligent algorithm has the characteristics of fast computing speed and strong searching ability, which can make up for the shortcomings of the traditional algorithm. In this study, the improved sparrow algorithm (Issa) combining Cauchy mutation and reverse learning strategy is used to solve the flood control optimization problem of reservoir groups. This study takes Sanmenxia Reservoir and Xiaolangdi Reservoir on the mainstream of the Yellow River as the research object and Huayuankou as the downstream control point to establish a joint flood control optimization operation model of cascade reservoirs. The results of the improved sparrow algorithm (Issa), particle swarm optimization (POS) and sparrow algorithm (ssa) are compared and analyzed. The results show that when the improved Issa algorithm is used to solve the problem, the maximum flood peak flow of the garden entrance control point is 11,676.3 m(3), and the peak cutting rate is 48%. The optimization effect is obviously better than the other two algorithms. This study provides a new and effective way to solve the problem of flood control optimization of reservoir groups.

关键词： Sanmenxia Reservoir Xiaolangdi Reservoir flood control operation ssa algorithm Issa algorithm

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Modelling of an imprecise sustainable production control problem with interval valued demand via improved centre-radius technique and sparrow search algorithm

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Scientific reports 2025年第1期15卷 19450页

作者： Hachen Ali Md Sadikur Rahman Ali Akbar Shaikh Adel Fahad Alrasheedi Jeonghwan Gwak Department of Mathematics The University of Burdwan Burdwan 713104 West Bengal India. Department of Mathematics Khalisani Mahavidyalaya Khalisani Chandannagar Hooghly 712138 West Bengal India. Department of Mathematics The University of Burdwan Burdwan 713104 West Bengal India. aakbarshaikh@***. Department of Statistics and Operations Research College of Science King Saud University P.O. Box 2455 Riyadh 11451 Saudi Arabia. Department of Biomedical Engineering Korea National University of Transportation Chungju 27469 Korea. Department of AI Robotics Engineering Korea National University of Transportation Chungju 27469 Korea. Department of IT & Energy Convergence (BK21 FOUR) Korea National University of Transportation Chungju 27469 Korea.

The modelling and optimization of a manufacturing systems in the context of sustainable production under uncertainty remain a pivotal focus in control theory. The goal of this research is to develop a robust decision-making framework for a production-inventory system characterised by imperfect production with reworking processes, and interval valued non-linear demand rate which is dependent on green level, selling price, warranty period, and time. This study also considers the impact of carbon emission regulation taxes to demonstrate how CO2 emission control influences the best-found policy of the proposed system. To fulfil the goal, an interval-valued optimal control problem (IVOCP) is constructed using generalised variational principle and corresponding highly nonlinear interval maximization problem is obtained. To tackle this interval optimisation problem, an improved c-r optimisation technique and the meta-heuristic algorithm Sparrow Search algorithm (ssa) are employed. The best-found solution for the corresponding problem is numerically illustrated through four distinct scenarios based on the presence of green investment levels and warranty periods in the demand rate. The obtained best found results are compared by some other metaheuristic algorithms. Additionally, statistical tests and non-parametric tests are conducted to assess the effectiveness, consistency, and stability of the algorithms. Furthermore, sensitivity analyses have been made to observe how inventory system parameters impact the optimal policy. Based on these analyses, managerial insights are derived to aid in decision-making processes.

关键词： Carbon-emission Greenness Imperfect production with reworking Interval variational calculus ssa algorithm Warranty period

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A novel non-isolated positive output voltage buck-boost converter

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WORLD JOURNAL OF ENGINEERING 2019年第1期16卷 201-211页

作者： Mohapatra, Tapas Kumar Dey, Asim Kumar Mohapatra, Krushna Keshab Sahu, Binod Siksha O Anusandhan Univ Dept Elect Engn Bhubaneswar Orissa India

Purpose A two switches non-isolated DC-DC novel buck-boost converter for charging the battery of electric vehicle is projected in this paper. The performance of the converter is compared with conventional buck-boost and transformer-less P/O buck-boost converter by Shan and Faqiang. The detail operation and performance analysis of the proposed converter is described both in continuous conduction mode and discontinuous conduction mode. A state space model and simulation model is designed in MATLAB. The PID controller parameters are tuned using Single-objective Salp swarm optimization algorithm using MATLAB. The controller is implemented using DSP board. The hardware and simulation results are projected in the paper to validate the effectiveness of the proposed buck-boost converter. A comparison analysis is projected among conventional converter and Shan & Faqiang converter. Design/methodology/approach The converter state space model is designed and simulation model is also developed in MATALAB. The controller is implemented using DSP board. The parameters are obtained using optimization technique using ssa algorithm. The hardware design is also implemented, and the result is compared with the Shan and Faqiang converter. The efficiency of the converter is also tested. Findings The converter is providing a higher efficiency. The inductor current is also positive in both buck and boost mode. The robustness of the controller is better for a wide range of variation of input voltage because the output voltage remains almost constant. Therefore, this is very suitable for battery charging and PV module application. Practical implications For battery charging from PV module where voltage fluctuation is frequent. Social implications The authors can use household applications to charge the battery using PV module. Originality/value The converter design concept is new. Optimization is used to find the parameters of the controllers and is implemented in hardware design. The parame

关键词： Closed loop control Continuous conduction mode (CCM) Positive output voltage ssa algorithm Buck-boost converter

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