Data Mining and Knowledge Engineering

T. Anandhakrishnan ¹, A. Saradha ¹

Affiliations
1 Department of Computer Science & Engineering, Institute of Road and Transport Technology, Erode, IN

Abstract

Electricity can be generated by a variety of ways. Wind power has many characteristics which other fossil energy does not have, such as clean, intermittent and randomness. This is because the wind is a natural phenomenon. Wind energy converts into mechanical energy in the way that wind blow through fans to drive rotor rotation. The reason why the demand for wind power around the world grows involves many aspects, including the shortage of energy, change in climate, the progress of economy and technology, etc. Due to wind is intermittent and less dispatchable, wind power fluctuates as the wind fluctuating and is uncontrollable. The way to solve the problem is forecasting the wind power. The wind speed and wind power are considered as the main input to forecasting models. The new forecasting model is adaboost with Back propagation NN. The new model mainly focusing the speed and accuracy. The new algorithm adaboost with Back propagation NN will improve the accuracy of the forecasting power with the forecasting wind. This is because using the forecasting wind speed instead of the original one can reduce the error which is caused by the training data and the noise which is produced in sampling process or data transmission.

Keywords

Wind Energy, Wind Power, Adaboost, Back-Propagation Nn.

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K. Karpagam ¹, A. Saradha ²

Affiliations
1 Department of Master of Computer Application, Dr. Mahalingam College of Engineering & Technology, Pollachi, IN
2 Department of Computer science and Engineering, Institute of Road and Transport Technology, Erode., IN

Abstract

Document clustering or text clustering is an unsupervised technique and it is used to grouping the documents of same context. Document clustering algorithms are widely used in web searching engines to produce results relevant to a query. Today, the information in websites is growing in huge size and it leads to the process of managing, retrieve the required and updated information is a tedious task. Also necessary to obtain the exact information required by the user from the documents. Recently optimization algorithms are introduced and are applied to the clustering algorithms. The Genetic Algorithm and Cuckoo Search algorithms are meta-heuristic optimization algorithms and are used to obtain the optimum solutions. In this paper, Genetic Algorithm and Cuckoo Search algorithm based Domain-specific Keyword Similarity based Knowledgebase Creation algorithm are proposed to optimize the document clustering to answers the question answering system. The experimental were conducted on benchmark datasets and the performance was analyzed in terms of Precision, Recall, F1, Missrate, Fallout and Purity.

Keywords

Cuckoo Search, Document Clustering, Genetic Algorithm, Information Processing Knowledge Base, Text Mining.

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