scholarly journals Data Mining Model Based on Improved Ant Colony Algorithm

2020 ◽  
Vol 1693 ◽  
pp. 012103
Author(s):  
Haoning Wu
Keyword(s):  
Data Mining ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Model Based ◽  
Mining Model ◽  
Improved Ant Colony Algorithm

Application and Analysis of Improved Ant Colony Algorithm in Physical Fitness Test

2021 ◽  
Vol 7 (5) ◽  
pp. 5009-5017
Author(s):  
Lili Zhang
Keyword(s):  
Physical Fitness ◽  
Shortest Path ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Physical Fitness Test ◽  
Physical Test ◽  
Fitness Test ◽  
Model Based ◽  
Physical Tests ◽  
Improved Ant Colony Algorithm

Objectives: The ant colony algorithm is an algorithm that the Italian scholar sums up by studying the living habits of the creatures, and algorithm model established by inspiration according to ants finding things in the shortest path. Methods: In this paper, through the establishment of algorithm model based on an ant colony algorithm, all kinds of problems in physical fitness test were solved, which makes the physical test more efficient and convenient. Results: Through the testing and use of the algorithm model, it is found that the ant colony algorithm established in this paper can meet the requirements, can plan the information of physical fitness test as a whole, Conclusion: and help to deal with the problems of physical tests, so it is a good performance algorithm.

Adaptive Cloud Resource Scheduling Model Based on Improved Ant Colony Algorithm

2020 ◽  
Vol 57 (1) ◽  
pp. 010603
Author(s):  
聂清彬 Nie Qingbin ◽  
潘峰 Pan Feng ◽  
吴嘉诚 Wu Jiacheng ◽  
曹耀钦 Cao Yaoqin
Keyword(s):  
Ant Colony Algorithm ◽  
Resource Scheduling ◽  
Ant Colony ◽  
Model Based ◽  
Scheduling Model ◽  
Cloud Resource ◽  
Cloud Resource Scheduling ◽  
Improved Ant Colony Algorithm

scholarly journals Research on Balance Control of Freestyle Skiing Aerial Skills Based on Ant Colony Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Wang Jun ◽  
Wenli Song ◽  
Zhipeng Li
Keyword(s):  
Data Mining ◽  
Ant Colony Algorithm ◽  
Clustering Algorithm ◽  
Balance Control ◽  
Poor Performance ◽  
Ant Colony ◽  
Strong Response ◽  
Good Reliability ◽  
Good Convergence ◽  
Mining Model

Aiming at solving the problem of poor performance of airborne freestyle skiing balance, this paper presents the research of airborne freestyle skiing balance control based on ant colony algorithm. On the basis of defining the trajectory division of the airborne balance of freestyle skiing and the track of the center of gravity of the human body, a sensor is used to collect the data of the airborne balance of freestyle skiing, and the moving average, denoising, and normalizing processes are done. The training label of the ant colony algorithm is made by the analog signal matrix, the implementation foreground of the key posture frame of freestyle skiing is extracted, the disturbed area in the key posture frame is removed by the clustering algorithm, and the key posture area of freestyle skiing is obtained. The incremental clustering of the data of the key posture area of freestyle skiing is conducted, the incremental posture data mining model of freestyle skiing is established, the mining parameters are input into the mining model, and the incremental data mining is realized by the ant colony algorithm to complete the research on the control of the airborne balance of freestyle skiing. The results show that the proposed method has good reliability, good convergence, and strong response ability.

Research on Regional renewable sources planning Model Based on Improved Ant Colony Algorithm

2021 ◽  
Author(s):  
Xinpin Wang ◽  
Manxi Leng ◽  
Weiqiang Fu ◽  
Haoqi Wang ◽  
Yutong Xue ◽  
...  
Keyword(s):  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Planning Model ◽  
Renewable Sources ◽  
Model Based ◽  
Improved Ant Colony Algorithm

Advanced ant colony algorithm for high dimensional abnormal data mining in Internet of things

2022 ◽  
pp. 1-10
Author(s):  
Huixian Wang ◽  
Hongjiang Zheng
Keyword(s):  
Data Mining ◽  
Internet Of Things ◽  
Ant Colony Algorithm ◽  
Transition Probability ◽  
Ant Colony ◽  
High Dimensional ◽  
Average Error ◽  
Mining Depth ◽  
The Internet Of Things ◽  
Improved Ant Colony Algorithm

This paper proposes a deep mining method of high-dimensional abnormal data in Internet of things based on improved ant colony algorithm. Preprocess the high-dimensional abnormal data of the Internet of things and extract the data correlation feature quantity; The ant colony algorithm is improved by updating the pheromone and state transition probability; With the help of the improved ant colony algorithm, the feature response signal of high-dimensional abnormal data in Internet of things is extracted, the judgment threshold of high-dimensional abnormal data in Internet of things is determined, and the objective function is constructed to optimize the mining depth, so as to realize the deep data mining. The results show that the average error of the proposed method is only 0.48%.

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