Informatics Publishing Limited

N. Sandhya ¹

Affiliations
1 MBA Department, REVA Institute of Science and Management, Yelahanka, Bangalore-560064, IN

Abstract

The business sector in India is highly promising in the present scenario. The impact of globalization has changed the business procedure in India in terms of psychology, methodology, technology, mindset, work culture etc. Newer challenges, newer opportunities are day-by-day in front of Indian industries, which are profitable and prospective. Major Service sectors like IT, banking, insurance, tourism and education have undergone significant changes. The huge population of India has created a large unsaturated market of consumers. This is one of the reasons why global companies are very much interested in doing business in India.

Keywords

Global Perspectives, Work Culture, Quality Education.

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K. Hari Prasada Raju ¹, N. Sandhya ², Raghav Mehra ³

Affiliations
1 Wells Fargo India Solutions Pvt Ltd, Hyderabad - 500081, Telangana, IN
2 CSE Department, VNRVJIET, Hyderabad - 500090, Telangana, IN
3 CSE Department, Bhagwant Institute of Technology, Muzaffarnagar - 251315, Uttar Pradesh,, IN

Abstract

Objectives: The model built in this paper is used to classify the rainfall datasets in identifying districts of more rainfall and of lesser rainfall in the state of Andhra Pradesh. Methods: In this paper support vector machine, random forest, Knearest neighbor and decision tree classification methods have been used to classify rainfall data sets which is divided into training set and test set for classification and later validation of the obtained results. Findings: Based on various statistical parameters like sensitivity, prevalence, detection rate, specificity, and detection prevalence it has been concluded that support vector machine classification methods is better than any other classification method used in the research. Rainfall data sets are used to initially build the classification model and the results are tested against the test set. Using the confusion matrix thus obtained the mentioned statistical parameters are obtained to establish the supremacy of support vector machine classification method. Applications: Examples of satellite imagery has become ever more significant in numerous application domains such as ecology monitoring and alternative discovery. Rainfall classification is the application used herein.

Keywords

Classification, Data Mining, Classifier, Support Vector Machines, SVM.

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G. Saravana Kumar ¹, N. Sandhya ², V. S. Krishna Priya ¹

Affiliations
1 Department of Instrumentation and Control Engineering, Tamilnadu College of Engineering, Coimbatore, IN
2 Department of Instrumentation and Control Engineering, Tamilnadu College of Engineering, Coimbatore, IN

Abstract

This paper is about comparison between PID tuning method and PI predictive control in the conical tank process. The level control becomes quite typical due to the nonlinear shape of tank. Many process industries use conical tanks because of its shape contributes to better drainage of solid mixtures, slurries and viscous liquids. So control of conical tank presents a challenging problem due to its non-linearity and constantly changing cross-section. A conventional PID controller is used to control the conical tank system based upon tuning rules. From the knowledge of ultimate gain and ultimate frequency, we can obtain the tuning parameters by using ZN-Closed loop method.  Predictive PI control (PIP) has the advantage that it manages to predict the measurement signal even when the process has along dead time and when the measurement signal is noisy.

Keywords

Conical Tank, ZN Tuning Method, PID Control, PIP (Predictive PI Control), MATLAB/SIMULINK.

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