Rajasthan Technical University

About: Rajasthan Technical University is a education organization based out in Kota, Rajasthan, India. It is known for research contribution in the topics: Photovoltaic system & PID controller. The organization has 716 authors who have published 1084 publications receiving 4530 citations. The organization is also known as: RTU.

Intelligent neighbourhood teaching learning based optimization algorithm

Abstract: Teaching Learning Based Optimization Algorithm (TLBOA) is an efficient approach of dealing with linear, nonlinear and multidimensional optimization problems. It depicts the classroom behaviour of teachers and students (learners). The algorithm is divided in two phases, namely Teacher phase and Learner phase. The position update process of learner phase is based on the difference vector of two randomly selected solutions, which improves the diversification ability of the algorithm. Further, in case of high step size, the solutions may skip the global optima. Therefore, to improve the exploitation ability and to control the step size, a new phase called as intelligent phase inspired from the Onlooker bee phase of Artificial Bee Colony optimization algorithm, is incorporated with the TLBO. In the propounded phase, intelligent solutions will be given more chances in participation of the position update process. This will leads to high convergence in the swarm. The performance of this propounded algorithm is calculated over 15 benchmark functions and compared with other state of art optimization algorithms namely TLBO, Gravitational Search Algorithm (GSA), and Grey Wolf Optimizer (GWO).

Static Synchronous Compensator Damping Controller Design Using Fast Output Sampling Feedback Technique

Abstract: In this article, the design of a damping controller for a static synchronous compensator using a fast output sampling feedback technique is presented. The proposed technique needs only the information of locally available signals, and moreover, by this technique, a very simple controller in the form of a simple gain matrix is obtained, which is effective over a range of operating conditions. Because of these two reasons, the control system designed by the proposed technique is very easy to implement. The effectiveness of the proposed technique has been validated through detailed non-linear simulation studies on the 10-machine 39-bus New England system.

Evaluation Of Distance Measures In Content Based Image Retrieval

Abstract: Content-Based Image retrieval (CBIR) is an application of computer vision which tries to cope up with the hindrance of image retrieval i.e. searching of an image from the large repositories. In CBIR, images are denoted as features in the dataset. The two key parameters involved in retrieving the actual content includes the extracting of image features and features matching. Once the image features are extracted, the homogeneous attributes are measured with the help of similarity metrics. Similarity matrix is one of the key issues in CBIR. Their exits number of similarity matrix. Most popularly used similarity metrics are described and evaluated in this paper. They are evaluated on standard Wang Image dataset which is considered as a benchmark database for CBIR. Result shows that Chebychev Metrics gives the highest average accuracy of 92.56% whereas in respect of response time, Euclidean Metrics gives the best time performance with average elapsed time of 1.275573 seconds.

Data Cleaning Mechanism for Big Data and Cloud Computing

Abstract: Data cleaning and data filtering mechanism are an important tool for IoT(Internet of Things) based Big Data and Cloud Computing technologies. In today's world, majority of the industries and sectors needs data's for processing and they find out potential customer for their businesses. With the exceptional growth in scale up of data's, increasing amount of training data set available for processing at Big Data and Cloud Computing side. In most of the data set, at least 10 % of data set are missing values, erroneous, in-complete, not suitable, noisy data or outliers. Data cleaning approach is used to remove outliers, missing values from the huge data set and correct information gathered. No data set provides right information with noisy or missing values. This paper deals with mechanism through programming concept to remove noisy or missing values in a heterogeneous data set under Big Data system and Cloud Computing. This paper deals with outlier analysis concept with respect of Big Data technologies.