Prediction of rockburst hazard based on particle swarm algorithm and neural network

Zhang, Meichang

doi:10.1007/s00521-021-06057-9

Cited by 43 publications

(21 citation statements)

References 22 publications

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“…Therefore, scholars often use other algorithms as assistance to improve the accuracy of prediction and evaluation. For example, Zhang (2021) established a regression model through BP network and used PSO algorithm to optimize connection weights to evaluate the slow convergence of BP network, in order to improve the accuracy of rockburst prediction [ 13 ]. Wang (2019) et al used LM algorithm to improve the operation efficiency and accuracy of traditional BP neural network and provided an effective theoretical basis and modeling method for risk prediction of power communication network [ 14 ].…”

Section: Introductionmentioning

confidence: 99%

[Retracted] Security and Privacy Risk Assessment of Energy Big Data in Cloud Environment

Shi

et al. 2021

Computational Intelligence and Neuroscience

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Considering the importance of energy in our lives and its impact on other critical infrastructures, this paper starts from the whole life cycle of big data and divides the security and privacy risk factors of energy big data into five stages: data collection, data transmission, data storage, data use, and data destruction. Integrating into the consideration of cloud environment, this paper fully analyzes the risk factors of each stage and establishes a risk assessment index system for the security and privacy of energy big data. According to the different degrees of risk impact, AHP method is used to give indexes weights, genetic algorithm is used to optimize the initial weights and thresholds of BP neural network, and then the optimized weights and thresholds are given to BP neural network, and the evaluation samples in the database are used to train it. Then, the trained model is used to evaluate a case to verify the applicability of the model.

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Section: Introductionmentioning

confidence: 99%

[Retracted] Security and Privacy Risk Assessment of Energy Big Data in Cloud Environment

Shi

et al. 2021

Computational Intelligence and Neuroscience

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“…The artificial neural network simulates the biological neural network from the perspective of informatics; the purpose of information processing is achieved by adjusting the connection mode within the network (Zhang, 2021). The ANN is one of the most popular neural networks, as an operation model; there are many nodes connected inside the neuron, and its structural principle is shown in Figure 1.…”

Section: Neural Network-cloud Modelmentioning

confidence: 99%

Prediction and evaluation of projectile damage in composite plates using the neural network–cloud model

Zeng

Liu

et al. 2023

Front. Mater.

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Composite plates are widely used in the aircraft manufacturing industry. The projectile damage of composite plates is affected by complex factors such as material, structure, impact velocity, and impact angle. A reliable method is needed for efficient structural health monitoring. In this paper, a composite plate damage prediction and evaluation model based on the cloud model and neural network is proposed; the five types of experimental characteristics are used as input parameters, and the depth and diameter of the damage area are used as output parameters to train the neural network–cloud model. This method transforms the quantitative data of impact damage of the composite plate into qualitative damage by introducing the cloud model, which makes the damage situation more intuitive. The results show that the accuracy of the prediction model is 97.23%, the accuracy of the evaluation model is 92.41%, and the comprehensive accuracy of the model is 89.85%. The composite damage prediction model has a good prediction performance.

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“…e other is the heuristic intelligent algorithm, such as genetic algorithm [8][9][10], simulated annealing algorithm [11][12][13], ant colony algorithm [14][15][16], and particle swarm algorithm [17][18][19].…”

Section: Hungarian Algorithm For Model Solutionmentioning

confidence: 99%

Optimization of Digital Management Path for Human Resource Performance Evaluation Based on Multiobjective Decision-Making Mathematical Model

Liu

Yong

2022

Mobile Information Systems

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Talent is an indispensable and important factor for the development and growth of an enterprise. Therefore, human resources have become an important resource of enterprises, and performance appraisal in human resource management has also become one of the important contents of modern enterprise management. Without a set of scientific and standardized performance appraisal systems, it will make it difficult for the daily human resource performance management of enterprises to achieve the expected goals. This study analyzes the actual needs, business processes, and existing problems of an enterprise in performance management and uses the multiobjective decision-making mathematical model to obtain an optimization plan for human resources performance assessment. Finally, a digital management system for enterprise performance appraisal is designed. The main work of this study is as follows: (1) based on the work characteristics of a certain enterprise, the key indicators of enterprise performance evaluation are analyzed; (2) a multiobjective decision-making mathematical model is constructed for the optimization of human resources performance evaluation; (3) the Hungarian algorithm is used to solve the construction The mathematical model of multiobjective decision-making can obtain the optimal work arrangement. This study combines performance appraisal with practical work and uses the proposed multiobjective decision-making mathematical model to obtain the optimization results of human resources, guide practical work, and improve the efficiency of enterprise operation.

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Prediction of rockburst hazard based on particle swarm algorithm and neural network

Cited by 43 publications

References 22 publications

[Retracted] Security and Privacy Risk Assessment of Energy Big Data in Cloud Environment

[Retracted] Security and Privacy Risk Assessment of Energy Big Data in Cloud Environment

Prediction and evaluation of projectile damage in composite plates using the neural network–cloud model

Optimization of Digital Management Path for Human Resource Performance Evaluation Based on Multiobjective Decision-Making Mathematical Model

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