In this paper, we introduce the concept of (4/3)? bandwidth interval based forecasting. The historical enrollments of the university of Alabama are used to illustrate the proposed method. In this paper we use the new ...In this paper, we introduce the concept of (4/3)? bandwidth interval based forecasting. The historical enrollments of the university of Alabama are used to illustrate the proposed method. In this paper we use the new simplified technique to find the fuzzy logical relations.展开更多
Target based association rules extract the correlation between targets in and around strategically specified regions. These rules can be used to predict and estimate the future results and find the faulty targets, etc...Target based association rules extract the correlation between targets in and around strategically specified regions. These rules can be used to predict and estimate the future results and find the faulty targets, etc. To extract these rules efficiently and effectively data preparation is required. The existing mechanisms of data preparation have the problem of redundancy in the data. As a consequence, extra energy is required for the sensors which used to monitor the targets. In this paper, authors propose a novel data preparation approach for target based association rule mining from the point of coverage wireless sensor networks, which reduces the redundancy in the data and thus enhances the performance of the network.展开更多
文摘In this paper, we introduce the concept of (4/3)? bandwidth interval based forecasting. The historical enrollments of the university of Alabama are used to illustrate the proposed method. In this paper we use the new simplified technique to find the fuzzy logical relations.
文摘Target based association rules extract the correlation between targets in and around strategically specified regions. These rules can be used to predict and estimate the future results and find the faulty targets, etc. To extract these rules efficiently and effectively data preparation is required. The existing mechanisms of data preparation have the problem of redundancy in the data. As a consequence, extra energy is required for the sensors which used to monitor the targets. In this paper, authors propose a novel data preparation approach for target based association rule mining from the point of coverage wireless sensor networks, which reduces the redundancy in the data and thus enhances the performance of the network.
