A Survey on Web Usage Mining

Now a day World Wide Web become very popular and interactive for transferring of information. The web is huge, diverse and active and thus increases the scalability, multimedia data and temporal matters. The growth of the web has outcome in a huge amount of information that is now freely offered for user access. The several kinds of data have to be handled and organized in a manner that they can be accessed by several users effectively and efficiently. So the usage of data mining methods and knowledge discovery on the web is now on the spotlight of a boosting number of researchers. Web usage mining is a kind of data mining method that can be useful in recommending the web usage patterns with the help of users2019; session and behavior. Web usage mining includes three process, namely, preprocessing, pattern discovery and pattern analysis. There are different techniques already exists for web usage mining. Those existing techniques have their own advantages and disadvantages. This paper presents a survey on some of the existing web usage mining techniques

Research Article Improving the Efficiency and Power Factor of Induction Motor using Enhanced ABC with Aid of GA

Abstract: This study presents a technique for improving the efficiency and power factor of induction motor. In the proposed method, enhanced Artificial Bee Colony (ABC) with the aid of Genetic Algorithm (GA) algorithm is used to optimize the induction motor's parameters at various loading points. In the proposed algorithm, employed bees are generated the new solution for the input parameters by using GA. In the proposed method, GA is used for controlling the frequency of perturbation and improving the searching performance of ABC. The proposed method is used to provide the exact parameters from the optimized parameter values for all type of loading conditions. The parameters of induction motors are determined from the current, voltage, power loss, stray load losses and etc. The proposed technique is implemented in MATLAB platform and performance is evaluated. The performance of the proposed method is compared with ABC, FLC and integrated technique

INVESTIGATION OF ATTRIBUTE AIDED DATA AGGREGATION OVER DYNAMIC ROUTING IN WIRELESS SENSOR NETWORKS

Wireless Sensor Networks (WSNs) comprises several sensor nodes. The energy consumption is the major issue in WSNs. Data aggregation is a main method to conserve energy in WSN and minimizes the number of transmissions and then to save energy. This paper focuses on various data aggregation algorithms and protocols to collect and aggregate data in an efficient way so that life energy is increased. And, the varieties of algorithms are compared by of performance measures such as latency, data accuracy and life time. To make data aggregation more efficient a potential-based dynamic routing is elaborated to support an Attribute - aware Data Aggregation (ADA) strategy which is relied upon the idea of potential in physics and pheromone in an ant colony