Research on dynamic handover decision algorithm based on fuzzy logic control in mobile FSO networks

Qian, Peiheng; Shang, Tao; Gao, Yan; Ding, Guangfei

doi:10.1007/s11107-020-00920-w

Cited by 6 publications

(4 citation statements)

References 19 publications

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“…Among them, the method of deleting attributes with missing values is suitable for very few attributes. Value contains a large number of missing values, to obtain more effective results [ 12 ]. The common missing value completion methods include mean value interpolation, mode interpolation, and intermediate value interpolation.…”

Section: Database Establishmentmentioning

confidence: 99%

Application of Motion Effect Evaluation Algorithm Based on Random Forest

Dong

2022

Computational Intelligence and Neuroscience

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The development of big data technology makes the feature selection technology gradually perfect. The advantages of different feature selection technologies are different. Among them, random forest algorithm belongs to integrated feature selection algorithm. Integrated processing of classification results can screen out the most representative feature impact. Based on this background and random forest algorithm, this paper analyzes the evaluation of motion effect. After the measurement, this paper obtains the body data before and after the training. After the calculation, the change data of the body index are determined. The random forest feature selection method is used as the carrier to determine the corresponding index attribute set. In the process of data set input, the corresponding whole input data set is formed through data classification. The completion of training, through the comparative experiment, is conducive to clear the degree of influence of physical indicators and then complete the exercise effect evaluation. The research shows that the random forest algorithm has significant advantages in the evaluation of sports effect and can effectively improve the accuracy of classification.

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Section: Database Establishmentmentioning

confidence: 99%

Application of Motion Effect Evaluation Algorithm Based on Random Forest

Dong

2022

Computational Intelligence and Neuroscience

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“…e distance between the overlapping data object and part B data object must be greater than the width of the overlapping area. Considering specific data objects with less than l or equal composite spacing, it is not necessary to evaluate whether the two can be combined [13]. Two attribute data objects can be removed from the priority, and the recovery time can be reduced by adjusting the priority accordingly.…”

Section: Optimization Of Rural Tourism Feature Subalgorithmmentioning

confidence: 99%

Classification of Rural Tourism Features Based on Hierarchical Clustering Analysis Knowledge Recognition Algorithm

Wang

Sui-ying

Chen

et al. 2022

Mathematical Problems in Engineering

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The vigorous development of tourism has made rural tourism a highlight of the new era. In order to better realize the classification of rural tourism features, this paper proposes a knowledge recognition algorithm based on hierarchical clustering analysis. Firstly, the rationality of the optimization of the rural tourism feature algorithm is analyzed in this paper; secondly, the rural tourism feature classification index system is constructed based on the hierarchical clustering analysis; finally, the index weights are clearly divided according to the characteristics through the hierarchical clustering analysis of the knowledge identification algorithm. According to the specialties of hierarchical clustering analysis, the criteria of the algorithm are determined, and the characteristics of rural tourism are carefully classified. Rural tourists can visit different scenic spots in high density and improve the mobility of rural tourism. The experimental results show that: through the analysis of the characteristic classification data of the Rural Tourism College in this paper, it can be seen that the average daily income of the scenic spot is higher than that of the traditional rural scenic spot. The average daily income of rural tourism has increased by more than 261,900 yuan, which has largely promoted the development trend of rural tourism in my country. It is proved that the hierarchical clustering analysis method is helpful for rational zoning and serious thinking about the characteristics of rural tourism. This paper provides a reference for promoting the classification of rural tourism.

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“…Al-Salhi et al based on logistic regression algorithm and decision tree algorithm, analysis of prognostic factors for breast cancer [10]. Qian et al proposed a safe outsourcing drug detection system based on DT-PKC encryption system, the system classification is completed by the SVM algorithm, and privacy protection is achieved by designing a secure multiparty protocol [11]. Yao et al based on the fully homomorphic encryption algorithm, in the ciphertext domain, the minor allele frequencies and chi-square detection in genome-wide association analysis are calculated and support the calculation of Hamming distance and approximate edit distance for encrypted DNA sequences [12].…”

Section: Literature Reviewmentioning

confidence: 99%

Computer Network Confidential Information Security Based on Big Data Clustering Algorithm

Liu

2022

Wireless Communications and Mobile Computing

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Attacks on network systems are becoming more and more common, the current state of increasingly sophisticated attack methods, the emergence of intrusion prevention technology is the inevitable result of the development of computer technology and network technology, and research on intrusion prevention has become a new focus of network security technology research in recent years. In order to ensure the security of computer network confidential information, the authors propose a semisupervised clustering intrusion detection algorithm. An overview of machine learning, followed by an explanation of the theory of cluster analysis, simulation experiments were carried out using the K -means algorithm and the semisupervised clustering algorithm proposed by the author, for 10,000 records, the K -means clustering algorithm and the semisupervised clustering algorithm described in this paper are used, respectively, and intrusion detection data tests were performed. At the same time, different K values were selected, three datasets were selected from “kddcup.newtestdata_10_percent_corrected,” the test data were tested separately, and their average value was taken as the test result. From the simulation results, the detection rate of the semisupervised clustering algorithm is higher than that of the K -means clustering algorithm, and the false alarm rate and K -means algorithms have also been improved. Therefore, the author’s semisupervised algorithm enhances the stability of the system, and the performance of the K -means algorithm is improved to a certain extent. When the value of K gradually increases, the false alarm rate also increases; however, when K is 20, the detection rate is maximized, from this, it can be known that when K is 20, its detection rate reaches 91.76%, and the false alarm rate is 8.54%. The detection rate of the author’s algorithm is significantly higher than the other two algorithms, the false positive rate is slightly higher than K -means, and the false positive rate is lower than that of the other algorithm, proving the superior performance of our algorithm.

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Research on dynamic handover decision algorithm based on fuzzy logic control in mobile FSO networks

Cited by 6 publications

References 19 publications

Application of Motion Effect Evaluation Algorithm Based on Random Forest

Application of Motion Effect Evaluation Algorithm Based on Random Forest

Classification of Rural Tourism Features Based on Hierarchical Clustering Analysis Knowledge Recognition Algorithm

Computer Network Confidential Information Security Based on Big Data Clustering Algorithm

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