A Novel Hybrid Approach of Gravitational Search Algorithm and Decision Tree for Twitter Spammer Detection

2021 ◽  
Author(s):  
Luis Vives ◽  
Gurpreet Singh Tuteja ◽  
A. Sai Manideep ◽  
Sonika Jindal ◽  
Navjot Sidhu ◽  
...  
Keyword(s):  
Decision Tree ◽  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Hybrid Approach ◽  
Gravitational Search

scholarly journals Identification of CTQs for Complex Products Based on Mutual Information and Improved Gravitational Search Algorithm

2015 ◽  
Vol 2015 ◽  
pp. 1-6 ◽  
Author(s):  
Huaqiang Wang ◽  
Lijun Liang ◽  
Zhanwen Niu ◽  
Zhen He
Keyword(s):  
Mutual Information ◽  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Hybrid Approach ◽  
Data Sets ◽  
Complex Products ◽  
Information Relevance ◽  
Tenfold Cross Validation ◽  
Gravitational Search ◽  
Classification Capability

The identification of CTQs for complex products is the first step to implement quality control. To improve the efficiency and accuracy of CTQs identification, we propose a novel hybrid approach based on mutual information and improved gravitational search algorithm, which has advantages of filter and wrapper. At first, the information relevance and redundancy are measured by mutual information. Then, the improved gravitational search algorithm is used to search the CTQs. Experimentation is carried out using 2 UCI data sets, and the classification capability of CTQs is tested by SVM and tenfold cross validation. The results show that the presented method is verified to be effective and practically applicable.

Analysis of Optimal Power Flow Using Gravitational Search Algorithm

2016 ◽  
Vol 3 (4) ◽  
pp. 1-11
Author(s):  
M. Lakshmikantha Reddy ◽  
◽  
M. Ramprasad Reddy ◽  
V.C. Veera Reddy ◽  
◽  
...  
Keyword(s):  
Power Flow ◽  
Optimal Power Flow ◽  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Optimal Power ◽  
Gravitational Search

Automatic Mining of Quantitative Association Rules with Gravitational Search Algorithm

2017 ◽  
Vol 27 (03) ◽  
pp. 343-372 ◽  
Author(s):  
Umit Can ◽  
Bilal Alatas
Keyword(s):  
Association Rules ◽  
Optimization Problems ◽  
Search Algorithm ◽  
Fitness Function ◽  
Optimization Algorithms ◽  
Gravitational Search Algorithm ◽  
Search Space ◽  
Search Method ◽  
Quantitative Association Rules ◽  
Gravitational Search

The classical optimization algorithms are not efficient in solving complex search and optimization problems. Thus, some heuristic optimization algorithms have been proposed. In this paper, exploration of association rules within numerical databases with Gravitational Search Algorithm (GSA) has been firstly performed. GSA has been designed as search method for quantitative association rules from the databases which can be regarded as search space. Furthermore, determining the minimum values of confidence and support for every database which is a hard job has been eliminated by GSA. Apart from this, the fitness function used for GSA is very flexible. According to the interested problem, some parameters can be removed from or added to the fitness function. The range values of the attributes have been automatically adjusted during the time of mining of the rules. That is why there is not any requirements for the pre-processing of the data. Attributes interaction problem has also been eliminated with the designed GSA. GSA has been tested with four real databases and promising results have been obtained. GSA seems an effective search method for complex numerical sequential patterns mining, numerical classification rules mining, and clustering rules mining tasks of data mining.

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