The relevant experimental data of the fouling formation process of a heat exchanger were obtained through the fouling monitoring experimental platform. Whereafter, with regard to the conventional particle swarm optimi...
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The relevant experimental data of the fouling formation process of a heat exchanger were obtained through the fouling monitoring experimental platform. Whereafter, with regard to the conventional particle swarm optimization (PSO) algorithm, this study commenced from the iteration formula and innovatively presented an optimization approach for improving the inertia weight, thereby obtaining the improved particle swarm optimization (IPSO) algorithm. The wavelet neural network (WNN) was optimized through the application of the IPSO-WNN algorithm, resulting in the development of the IPSO-WNN model. Utilizing this model, a predictive model for fouling thermal resistance was constructed, incorporating input variables such as conductivity, pH, dissolved oxygen, average wall temperature, and bulk temperature, while the output variable represented fouling thermal resistance. Comparative analyses demonstrated that the IPSO-WNN model exhibited superior prediction accuracy and robust generalization capabilities to that of the conventional WNN and PSO-WNN models, as evidenced by significantly lower values across all indicators, including MAPE, MAE, and RMSE. The IPSO algorithm effectively optimized the initial parameters of the WNN, addressing the challenge of local minimum and enhancing the model's overall capacity to identify optimal solutions. This model effectively captures the dynamic trends of fouling thermal resistance during its growth stage and approaches the asymptotic value in the stable stage. Precise prediction models for heat exchanger fouling contribute valuable insights for its prediction in practical industrial applications.
With the continuous improvement of domestic processor performance and the continuous improvement of software ecology, the domestic e‐government field is increasing the promotion of localization, information products ...
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With the continuous improvement of domestic processor performance and the continuous improvement of software ecology, the domestic e‐government field is increasing the promotion of localization, information products based on domestic processors have been applied in batches, and the key information infrastructure of related key industries is carrying out domestic processor applications. Based on the domestic DSP chip FT‐M7002, C language and assembly language code are implemented and performance optimized for functions of basic algorithms such as matrix factorization, solving linear equations and filters. Huawei Kunpeng Server Project has developed image processing and signal processing function libraries such as HMPP on Huawei Kunpeng Server, and has obtained good research results.
Based on the background of dynamic mining pressure monitoring and pressure prediction research on the No. 232205 working face of the Meihuajing coal mine, this study systematically investigates the predictive model of...
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Based on the background of dynamic mining pressure monitoring and pressure prediction research on the No. 232205 working face of the Meihuajing coal mine, this study systematically investigates the predictive model of mining pressure manifestation on the working face of the Meihuajing coal mine by integrating methods such as engineering investigation, theoretical analysis, and mathematical modeling. A mining pressure manifestation prediction method based on IA-PSO-BP is proposed. The IA-PSO optimizationalgorithm is applied to optimize the hyperparameters of the BP neural network, and the working face mining pressure prediction model based on IA-PSO-BP is established. The mean absolute error (MAE), mean square error (MSE), and coefficient of determination (R2) are selected as evaluation indicators to compare the prediction performance of the BP model, PSO-BP model, and IA-PSO-BP model. The experimental results of the model show that the convergence speed of the IA-PSO-BP model is about eight times faster than that of the BP model and two times faster than that of the PSO-BP model. Compared with the BP and PSO-BP models, the IA-PSO-BP model has the smallest MAE and MSE and the largest R2 on the three different data sets of the test set, indicating significantly improved prediction accuracy. The predicted results conform to the periodic variation pattern of mining pressure data and are consistent with the actual situation in the coal mine.
The principles of G.729 algorithm are analyzed. It proposes an optimal approach of adaptive codebook search. Realized on fixed point DSP TMS320VC5410,the searching time of the optimal algorithm is thus significantly d...
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The principles of G.729 algorithm are analyzed. It proposes an optimal approach of adaptive codebook search. Realized on fixed point DSP TMS320VC5410,the searching time of the optimal algorithm is thus significantly decreased,and the result shows that the speech quality is not decreased.
Amazons is a computerized board game with complex positions that are highly challenging for humans. In this paper, we propose an efficient optimization of the Monte Carlo tree search (MCTS) algorithm for Amazons, fusi...
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Amazons is a computerized board game with complex positions that are highly challenging for humans. In this paper, we propose an efficient optimization of the Monte Carlo tree search (MCTS) algorithm for Amazons, fusing the 'Move Groups' strategy and the 'Parallel Evaluation' optimization strategy (MG-PEO). Specifically, we explain the high efficiency of the Move Groups strategy by defining a new criterion: the winning convergence distance. We also highlight the strategy's potential issue of falling into a local optimum and propose that the Parallel Evaluation mechanism can compensate for this shortcoming. Moreover, We conducted rigorous performance analysis and experiments. Performance analysis results indicate that the MCTS algorithm with the Move Groups strategy can improve the playing ability of the Amazons game by 20-30 times compared to the traditional MCTS algorithm. The Parallel Evaluation optimization further enhances the playing ability of the Amazons game by 2-3 times. Experimental results show that the MCTS algorithm with the MG-PEO strategy achieves a 23% higher game-winning rate on average compared to the traditional MCTS algorithm. Additionally, the MG-PEO Amazons program proposed in this paper won first prize in the Amazons Competition at the 2023 China Collegiate Computer Games Championship & National Computer Games Tournament.
This study explores the application of double-walled carbon nanotubes (DWCNTs) in underwater acoustic materials, aiming to overcome the low-frequency absorption limitations of traditional materials. Four main aspects ...
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This study explores the application of double-walled carbon nanotubes (DWCNTs) in underwater acoustic materials, aiming to overcome the low-frequency absorption limitations of traditional materials. Four main aspects were investigated: first, the mechanical properties of armchair-type DWCNTs were calculated based on molecular dynamics, and the equivalent mechanical parameters of the DWCNTs-reinforced rubber composites were computed by the Halpin-Tsai model. Secondly, a 6 × 6 transfer matrix model based on orthotropic anisotropic materials was established to predict sound absorption properties, validated by COMSOL Multiphysics simulations. Again, the influence laws of six micro-macro key parameters of the reinforcing materials on the sound absorption characteristics were explored. Finally, a comprehensive multi-gradient and multi-parameter optimization study of the underwater acoustic functional material was carried out by the Bayesian optimization and Hyperband (BOHB) optimizationalgorithm. The absorption bandwidth (α ≥ 0.65) of the optimized underwater acoustic functional composites spans from 0.299 kHz to 20 kHz, indicating its broadband absorption capability for practical applications. These findings advance the development of enhanced underwater acoustic materials.
The article considers the task of optimization of the information processing algorithm for positioning of receiving antenna of stationary hydroacoustic complexes based on geochronotracking and statistical evaluation o...
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ISBN:
(数字)9781728149448
ISBN:
(纸本)9781728149455
The article considers the task of optimization of the information processing algorithm for positioning of receiving antenna of stationary hydroacoustic complexes based on geochronotracking and statistical evaluation of retrospective data on the functioning efficiency. The features of the algorithms for processing the positioning information of receiving antennas based on geochronotracking largely determine the effectiveness and accuracy of the process of purpose-aimed using of sonar systems. This fact has determined the need to set the corresponding optimization problem, establish the boundary conditions for its solution and search for the corresponding extreme points. This article is devoted to the consideration of the mathematical and systemological aspects of the presented optimization. It defines the main parameters and optimality conditions of the considered algorithm, takes into account the results of recent developments on the subject of geochronological tracking.
Big data is the inevitable outcome of the rapid development of modern information technology, effective analysis and processing of big data will not only bring great economic value, but will also promote social develo...
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Big data is the inevitable outcome of the rapid development of modern information technology, effective analysis and processing of big data will not only bring great economic value, but will also promote social development. Under the big data environment, the data scale, speed of emergence and its difficulty make optimizing issues very complex. In recent decades, genetic algorithm(GA), particle swarm optimization(PSO), ant colony optimization(ACO), Artificial Fish School algorithm, Bacteria Foraging optimizationalgorithm(BFOA), artificial neural networks(ANNs) and other multi-population intelligent algorithms appeared. In this paper, several typical intelligent optimizationalgorithms are introduced, including genetic algorithm, particle swarm optimizationalgorithm, ant colony algorithm, artificial fish swarm algorithm and bacterial foraging algorithm. The basic principles of five algorithms are described respectively, along with the direction of improvement and feasible applications.
Based on the characteristics of Einstein würfelt nicht!(EWN),this paper puts forward the UCT algorithm applied to EWN,and on its basis,an optimized UCT algorithm with the evaluation function and the dynamic searc...
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Based on the characteristics of Einstein würfelt nicht!(EWN),this paper puts forward the UCT algorithm applied to EWN,and on its basis,an optimized UCT algorithm with the evaluation function and the dynamic searching rounds is *** evaluation function is used to better evaluate the situation,and the dynamic searching rounds is used to reduce the average cost per game by a decay *** playing multiple games with the UCT algorithm,the optimized UCT algorithm proved to be effective in improving the strength of the EWN game system.
This paper discusses the use of genetic algorithms (GA) within the area of reliability, availability, maintainability and safety (RAMS) optimization. First, the multi-objective optimization problem is formulated in ge...
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This paper discusses the use of genetic algorithms (GA) within the area of reliability, availability, maintainability and safety (RAMS) optimization. First, the multi-objective optimization problem is formulated in general terms and two alternative approaches to its solution are illustrated. Then, the theory behind the operation of GA is presented. The steps of the algorithm are sketched to some details for both the traditional breeding procedure as well as for more sophisticated breeding procedures. The necessity of affine transforming the fitness function, object of the optimization, is discussed in detail, together with the transformation itself. In addition, how to handle constraints by the penalization approach is illustrated. Finally, specific metrics for measuring the performance of a genetic algorithm are introduced. (C) 2005 Elsevier Ltd. All rights reserved.
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