Performance Evaluation of Association Rule Mining with Enhanced Apriori Algorithm Incorporated with Artificial Bee Colony Optimization Algorithm
Journal Title: International Journal of Intelligent Engineering and Systems - Year 2017, Vol 10, Issue 2
Abstract
In data mining, association rules are produced in view of solid relations and regularities existing among the variables in extensive exchanges. These association rules go for extricating connections, frequent patterns and associations among the item sets in exchanges. Association rules are connected for use in different zones, for example, media transmission, hazard administration and so forth. One such territory where the association rules are vital is the stock market. In stock marketing, picking the right stock relies on upon the genuine stock quality and the capacity to pick the stock is urgent as it impacts the profit of investors. In this work, the proposed technique develops a novel and effective way to deal with producing optimal stock rules to help in the stock market prediction by utilizing Enhanced Apriori algorithm and Artificial Bee Colony Optimization (ABC) algorithm. In the result profit of PP, EMA, ROC and RSI for min-support 3, 4, 5 and 6 individually in rule mining for HCL stock market dataset is appeared with correlation of GA-Apriori algorithm, AGA- Enhanced Apriori algorithm and ABC- Enhanced Apriori algorithm. From this Artificial Bee Colony (ABC) optimization algorithm is performed when contrasting and different strategies and grant that strong association rules to be produced.
Authors and Affiliations
Ramani Selvanambi
Efficient Dissemination of Rainfall Forecasting to Safeguard Farmers from Crop Failure Using Optimized Neural Network Model
In the field of weather forecasting, especially in rainfall prediction many researchers employed different data mining techniques. There is numerous method of organizing agricultural engineering substance and it remains...
An Evolutionary Multi-Objective Approach for Resource Scheduling in Mobile Cloud Computing
Mobile cloud computing (MCC) is one of the evolving fields in recent years. The complexity of MCC made researchers to concentrate on efficient application development. In MCC, resource scheduling is treated as one of the...
Autonomous Distributed Power Control in Multi-Channel Cognitive Femtocell Network: Feasibility and Convergence
Dynamic user in mobile communication encourages the implementation of self-organized and non-cooperative distributed power control. To be implemented, the power control must meet the feasible and convergent conditions. F...
Base Station Positioning in Wireless Sensor Network to aid Cluster Head Selection Process
In this paper, we propose an (SAPSO) Self-Adaptive Particle Swarm Optimization algorithm to solve the base station positioning problem. This algorithm is used to minimize the distance between the base station and cluster...
Automatic Detection and Classification of Masses in Digital Mammograms
Breast Cancer is still one of the leading cancers in women. Mammography is the best tool for early detection of breast cancer. In this work methods for automatic detection and classification of masses into benign or mali...