Structural Simulation Model Updating Based on Improved MCMC Algorithm and Surrogate Model by MIAO Ji, DUAN Liping, LIU Jiming, LIN Siwei, ZHAO Jincheng

“…The results show that WOA can significantly improve the stability and convergence speed of the MCMC algorithm, the updating efficiency can be improved by 13.9% at most, and the maximum frequency errors of the simply supported beam model and the three-story steel frame model updated by the WO-MH algorithm are 0.009% and 2.41%, respectively. …”
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The algorithm for applying the process maturity model to improve business processes in organization by S. I. Artemyeva, G. S. Kublashvili, A. G. Zaitsev

“…The article considers the most popular maturity models. An algorithm for applying these models is developed. …”
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Model of Effective Business Formation by V. G. Khalin, G. V. Chernova, S. A. Kalayda

“…The authors propose a model for the formation of an effective business, using Pareto optimality and implemented on the basis of two developed Algorithms, which is illustrated by a numerical example.…”
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Integrated optimization model for production and equipment dispatching in underground mines by LI Guo-qing, HOU Jie, HU Nai-lian

“…The model was validated in a large gold mine in China to work out the optimal equipment scheduling plan. …”
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Apllication of optimization algorithms to improve the design of turnouts by B. E. Glyuzberg

“…One of the most important tasks for improving the infrastructure facility of railways is its optimization. …”
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Modeling and Simulation of English Speech Rationality Optimization Recognition Based on Improved Particle Filter Algorithm by Hui Dong

“…The system has reasonable recognition ability for general speech, and the improved particle filter algorithm evaluation method is further used to optimize the defect of the English speech rationality and high recognition error rate Related experiments have verified the effectiveness of the method.…”
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Data-driven continuous-time Hammerstein modeling with missing data using improved Archimedes optimization algorithm by Muhammad Shafiqul Islam, Mohd Ashraf Ahmad

“…This research introduces the improved Archimedes optimization algorithm (IAOA) for data-driven modeling of continuous-time Hammerstein models with missing data. …”
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Improve the Hunger Games search algorithm to optimize the GoogleNet model. by Yanqiu Li, Shizheng Qu, Huan Liu

“…The setting of parameter values will directly affect the performance of the neural network, and the manual parameter tuning speed is slow, and it is difficult to find the optimal combination of parameters. Based on this, this paper applies the improved Hunger Games search algorithm to find the optimal value of neural network parameters adaptively, and proposes an ATHGS-GoogleNet model. …”
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Environmental Impact Minimization Model for Storage Yard of In-Situ Produced PC Components: Comparison of Dung Beetle Algorithm and Improved Dung Beetle Algorithm by Jeeyoung Lim, Sunkuk Kim

“…As a result of applying the developed model, the optimization of the improved dung beetle optimization algorithm was verified to be efficient by improving the neighboring correlation by 22.79% and reducing carbon dioxide emissions by 18.33% compared to the dung beetle optimization algorithm. …”
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A Model Predictive Control to Improve Grid Resilience by Joseph Young, David G. Wilson, Wayne Weaver, Rush D. Robinett

“…The following article details a model predictive control (MPC) to improve grid resilience when faced with variable generation resources. …”
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Optimization Performance and Efficiency Improvement of Microgrid Scheduling Model by Honggang JIA, Zhuding WANG, Yuanyuan YUE, Huan YAN, Na YAN, Qiangfei CAO

“…First of all, considering the cost of electricity charges, the cost of energy storage regulation, the user’s inappropriate cost and the benefit of response subsidies, an optimization model with the goal of minimizing the daily comprehensive power consumption cost is established; Then, aiming at the problem that the global optimization ability of the standard differential evolution algorithm is insufficient and the solution efficiency needs to be improved, the scaling factor and crossover operator are optimized and improved to form an adaptive hybrid differential evolution algorithm; Finally, taking the micro grid system as an example, the operation optimization of energy storage and demand response and the comparative analysis of calculation examples are carried out.The results show that the proposed method is suitable for multi scenario computing and has high optimization performance and solving efficiency.…”
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Groundwater level prediction using an improved SVR model integrated with hybrid particle swarm optimization and firefly algorithm by Sandeep Samantaray, Abinash Sahoo, Falguni Baliarsingh

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DESIGN OF AN IMPROVED MODEL FOR CARDIOVASCULAR DISEASE DETECTION USING DEEP CANONICAL CORRELATION ANALYSIS AND BIOINSPIRED OPTIMIZATION by Prakash Chandra Sahoo, Binod Kumar Pattanayak, Rajani Kanta Mohanty, Ayasa Kanta Mohanty

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Pipeline corrosion rate prediction model using BP neural network based on improved sparrow search algorithm by Shuhui XIAO, Chuanjia DU, Chengjun WANG

“…Methods This paper proposes a pipeline corrosion rate prediction model using an optimized BP neural network based on an improved Sparrow Search Algorithm to address the aforementioned disadvantages. …”
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The optimization model of building construction based on BIM and improved NSGA-III algorithm by Meng Wang

“…Therefore, a multi-objective optimization model was constructed based on building information management technology, and an improved non-dominated sorting genetic algorithm III was introduced to optimize the model solution. …”
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Utilization of Machine-Learning-Based model Hybridized with Meta-Heuristic Frameworks for estimation of Unconfined Compressive Strength by She Wang, Qi Zhang

“…The current study considers the RBF-based machine learning model, whose parameters have been optimized using two enhanced metaheuristic frameworks: Improved Arithmetic Optimization Algorithm (IAOA) and Flying Foxes Optimization (FFO). …”
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An improved deep learning model for soybean future price prediction with hybrid data preprocessing strategy by Dingya CHEN, Hui LIU, Yanfei LI, Zhu DUAN

“…Finally, the high frequency component is decomposed secondarily using variational mode decomposition optimized by beluga whale optimization algorithm. In the deep learning prediction stage, a deep extreme learning machine optimized by the sparrow search algorithm was used to obtain the prediction results of all subseries and reconstructs them to obtain the final soybean future price prediction results. …”
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CMACGSA: Improved Gravitational Search Algorithm Based on Cerebellar Model Articulation Controller for Optimization by Nazmiye Ebru Bulut, Emre Dandil, Ugur Yuzgec, Alpaslan Duysak

“…Recent advances in the field often involve hybrid methods that combine several algorithms to improve performance. This study introduces an improved Gravitational Search Algorithm, named CMACGSA, which incorporates the Cerebellar Model Articulation Controller (CMAC)-a neural network model-to enhance the performance of Gravitational Search Algorithm (GSA). …”
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An advanced CNN-attention model with IFTTA optimization for prediction air consumption of relay nozzles by Shen Min, Shao Ning, Cao Yongbo, Xiong Xiaoshuang, Yang Xuezheng, Wang Zhen, Yu Lianqing

“…This paper proposes a Convolutional Neural Network (CNN)-Attention regression model to predict air consumption of the relay nozzle, enhancing accuracy and efficiency with an Improved Football Team Training Algorithm (IFTTA). …”
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Parameter Sensitivity Analysis and Algorithm Improvement of Optimization Scheduling Model for Cascade Pumping Stations by LIU Xiaolian, LI Zhenrong, WANG Xue-ni, ZHAI Yu, ZHANG Lei-ke, GUO Weiwei, TIAN Yu

“…ObjectiveThe low operating efficiency, massive energy consumption and large carbon emissions often exist in the operation of cascade pumping stations. To improve the operational efficiency of cascade pumping stations and vigorously promote dual carbon construction, an optimization scheduling model for cascade pumping stations was established with the goal of minimizing carbon emissions, and the Runge Kutta algorithm (RUN) was introduced to solve the model. …”
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