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ThesisItem Open Access Intuitionistic fuzzy and hesitant fuzzy sets based time series forecasting methods(G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2017-12) Bisht, Kamlesh; Sanjay KumarIn the present research work, various time series forecasting methods using intuitionistic fuzzy, hesitant fuzzy and dual hesitant fuzzy sets are developed to address issue of non stochastic uncertainty and non-stochastic hesitation. These methods are presented in form of various models. Model [1] and Model [4] are computational algorithm based higher order fuzzy time series forecasting models which are based on intuitionistic fuzzy and hesitant fuzzy respectively. Model [2] and Model [3] use hesitant fuzzy set to handle hesitancy in fuzzy time series forecasting. In the present research work, methodology of hesitant fuzzy time series forecasting method is also developed and presented in Model [5]. Model [6] is intuitionistic fuzzy time series forecasting model which is based on dual hesitant fuzzy set. Model [2], Model [3], Model [5] and Model [6] use max-min composition operation. Performance of these developed models over existing fuzzy time series and intuitionistic fuzzy time series forecasting methods is verified by implementing them on two time series data of University of Alabama and SBI share price. The outperformance of all models is tested using RMSE and AFER error measures. Validity of the developed models id tested using correlation coefficients, tracking signal, evaluation parameter and performance parameters. Superiority of developed models is also tested using two tailed t-test at the confidence level 1% and 5%. In forecasting enrollments of University of Alabama, the performance of Model [4] in terms of both RMSE and AFER is found better than model [1], Model [2], Model [3], Model [5] and Model [6]. In forecasting share prices of SBI, the performance of Model [6] in terms of both RMSE and AFER is found better than Model [1], Model [2], Model [3], Model [4] and Model [5]. In forecasting enrollments of University of Alabama, Model [1] outperforms over Model [2] but its performance is equally good as of Model [3], Model [4], Model [5] and Model [6]. Model [2] outperforms over Model [4] and Model [5] but its performance is good as Model [3] and Model [6]. Model [3] performs equally good as Model [4], Model [5] and Model [6]. Model [4] outperforms over Model [6] but its performance is good as Model [5]. Model [5] is equally good in performance as the Model [6]. In forecasting SBI share prices, Model [1] outperforms over Model [2], Model [3] but its performance is good as Model [4], Model [5]. Model [2] outperforms over Model [4], Model [5] and Model [6] but its performance is good as Model [3]. Model [3] outperforms over Model [4], Model [5] and Model [6]. Model [4] performed equally good as Model [5] and Model [6]. Model [5] outperforms over Model [6]. All developed models not only handle the non-stochastic uncertainty and hesitation but also enhance the accuracy in forecasted enrollments and financial time series data of SBI share price.ThesisItem Open Access Statistical evaluation of body paramaters in adolescent girls(G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2016-07) Joshi, Bhawana; Shukla, A.K.Adolescence is a developing stage and the transition period of adolescence encompasses multiple significant changes like physical, psychological and social that takes place between childhood and adulthood. Body composition & anthropometric parameters are the surrogate measures of metabolic changes that occur in this period of growth and maturation. The assessment of these parameters provides key information to understand the current as well as future health of adolescents. In India, adolescent girls need special attention in view of their role in shaping the health and well being of the present and future generations. Therefore, the present study was undertaken with the major objectives to find distribution pattern of several body parameters, study of inter-relationship between body composition and anthropometric parameters, comparison of body parameters in different age groups and development of prediction models for BF% using different body parameters of adolescent girls. Secondary data of adolescent girls related to Age, Height (H), Weight (W), Body Mass Index (BMI), Waist Circumference (WC), Hip Circumference (HC), Waist-to-Height Ratio (WHtR), Waist-to-Hip Ratio (WHR), Total Body Water Percentage (TBW%), Body Density (BD), and Body Fat Percentage (BF%) were used in this investigation. Data were analysed with help of various parametric and non-parametric statistical techniques using different software namely SAS, IBME SPSS Statistics 20, EasyFit 5.6 Professional and JMP. The following conclusions were drawn from this study. • None of the body parameters under study follow Normal Distribution in the Combined Age Group (13-17 years) as well as in different segments of age groups of adolescent girls which revealed that for statistical study of these parameters non-parametric test procedures should be preferably used by the researchers and nutritionist for more reliable results. • Best fitted distribution of BF% and BMI in different segments of age groups were found appropriate for the prediction of proportion of adolescent girls in different health status categories. Therefore, these distributions could be effectively used to examine the health status of adolescent girls in different populations. • Age, TBW% and BD showed significant negative correlation with BF% whereas W, BMI, WC, HC, WHR and WHR were significantly positively correlated with BF% in adolescent girls of Combined Age Group (13-17 years). • TBW% and BD showed a significant negative partial correlation with BF% when the effect of other body parameters were controlled together. • Significant difference were observed in different segments of age groups with respect to H,W ,BMI, HC,WHR, BF% and TBW% whereas no significant difference was observed with respect to WHtR & WC. • The best prediction model for BF% could be achieved using Multiple Linear Regression Models as compared to Linear Regression and Non Linear Regression Models. The findings of the present study are expected to provide a new direction to health planners and nutritionists for decision making in health related issues of adolescent girls.ThesisItem Open Access Fuzzy rule based modeling to study effect of distillery effluent on crop economic field(G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2017-07) Dhyani, Makrand; Sanjay KumarThesisItem Open Access Analysis and forecasting of financial time series using artificial neural network(G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2017-07) Chauhan, Shikha; Pal, A.K.Present work entitled “ANALYSIS AND FORECASTING OF FINANCIAL TIME SERIES USING ARTIFICIAL NEURAL NETWORK” treated the issue of developing an artificial neural network model which generates a buying signal based on Golden crossover and sell signal if 50 DMA crosses below 200 DMA and also, forecasts the stock index for future. Artificial neural networks are very good in the stock market prediction as they are non-linear and complex models. In this work, we have used the artificial neural network to predict the stock index and behavior (buy or sell signal) of financial time series. The presented study comprises five chapters. The first chapter is aimed to fulfill the basic need of introducing time series, artificial neural network and the use of neural network in the time series forecasting. Chapter two accomplished majority of passed research work related with the present work. Chapter three covers the material and methods used for the present study. We have presented the neural network for the prediction and simulated it in MATLAB software. Chapter four describes the result and discussion of the encountered taken in chapter three. The work has been summarized in chapter five. Along with the finding of the study, the literature used in the course of the study has been referred under the section of literature cited. The related study may be helpful for the investors of stock market to make wise decisions so that they can have maximum profit.ThesisItem Open Access On reliability modeling of complex systems: signature and fuzzy based expressions(G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2017-07) Akshay Kumar; Singh, S.B.The present research study is based on the development of reliability models with the help of UGF and fuzzy sets. In this study, eight different reliability models have been developed. Model-1 studies the reliability characteristic of sliding window coherent system which consists of n number of components connected in parallel configuration using UGF. Model-2 discusses the signature reliability of complex and k-out-of-n coherent system with the help of reliability functions. Model-3 focuses on reliability metrics of a sliding window coherent system in case of multiple failures. Model-4 deals with a linear multi-state sliding window coherent system which generalizes the consecutive k-out-of-r-from-n:F system in multi-state case. All the aforesaid models evaluated the signature, MTTF, Barlow-Proschan index and expected cost etc. Model-5 studies the reliability of two states consecutive sliding window system consisting of generalized linear multi-state sliding window system having m consecutive independent and identically distributed components. Model-6 introduces and studies the intervalvalued reliability of to 2-out-of-4 system with the help of reliability function using UGF. The considered system consists of 2 numbers of components connected in series. Model7 investigates the intuitionistic fuzzy reliability measure of a linear (circular) consecutive k-out-of-n:F system of non-identical elements with the Weibull lifetime distribution and Markov process. Model-8 deals with series, parallel and consecutive k-out-of-n: F systems, using triangular hesitant fuzzy number and Weibull distribution.ThesisItem Open Access Reliability modeling of repairable systems using interval valued universal generating function(G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2017-06) Renu; Singh, S.B.In this thesis authoress studied following two different models: (1) Reliability assessment of repairable parallel-series multi state system applying interval valued universal generating function. (2) Reliability evaluation of repairable weighted (u, v)-out-of-(x, y) system using interval valued universal generating function. Both models involve a comprehensive analysis of the systems using interval-valued universal generating function incorporating different types of uncertainties which have been removed by using probability intervals. In the first model, we have considered a repairable multi-state parallel-series system having two different uncertainties namely Aleatory and epistemic uncertainty. Probability intervals have been used to deal with these uncertainties. The failure rates ( ijk l ) and repair rates ( ijk m ) are taken in interval numbers. Using Laplace-Steiltjes transform probability intervals have been calculated. By using these probabilities, reliability, MTTF and sensitivity of the proposed system have been computed. In the second model, repairable weighted (u, v)-out-of-(x, y) system consisting of 6 components with two types of uncertainties has been studied. In this model different weights have been assigned to the components to evaluate the reliability and sensitivity of the system with the help of same methods as applied in model-1.ThesisItem Open Access A study of flow and heat transfer of nanofluid over a flat plate(G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2017-05) Upreti, Himanshu; Manoj KumarRecent work deals with the problem pertinent to flow and heat transfer of nanofluid flow over a flat porous plate under the influence of suction/injection, heat generation/absorption and viscous-Ohmic dissipation. The influences of these parameters and other factor governing the flow have been analyzed and their impact on velocity and thermal boundary layer is reveal through graphs. Moreover, the non-dimensional quantities i.e., skin friction coefficient and heat transfer rate (Nusselt number) have also been computed and included in this study. The study presented in the thesis includes five chapters. The first chapter aims to fulfill the basic need of introducing the various concepts and foundation needed for fluid mechanics. Chapter two throw light on majority of passed research work related with the present work. Chapter three covers the mathematical formulation of the problem and its detailed description. A proper description of used methodology, together with the details of the numerical solution is also presented. Chapter four describes the result and discussion of the considered problem taken in chapter three. The work has been summarized in chapter five. In along with the finding of the study, the literature used in the course of the study has been referred under the section of literature cited. The related study may be helpful to applied scientific fields and different branch of engineering and applied mathematics.ThesisItem Open Access A study of heat and mass transfer flow problem in nanofluid(G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2016-06) Rawat, Sawan Kumar; Manoj KumarThesisItem Open Access Numerical study of some flow problems in nanofluid(G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2017-04) Pandey, Alok Kumar; Manoj KumarIn the present study numerical scheme have been employed to analyze the boundary layer flow, heat and mass transfer flow past a nanofluid due to various geometries. The flow around immersed bodies in Newtonian and Non-Newtonian fluid streams are commonly encountered in many studies in medical arena, geophysics, mechanical engineering, hydrodynamics, chemical engineering and ocean engineering etc. The boundary layer flow of nanofluid around bodies of various geometries such as wedge, stretching cylinder, stretching surface, parallel plate and divergent/convergent channel have been discussed. The different flow conditions involve various physical phenomenon such as magnetic effect, velocity slip effect, thermal slip effect, suction/injection, Brownian motion and thermophoresis effects, porosity, buoyancy effect, heat generation/absorption, thermal radiation, chemical reaction, viscous dissipation, Ohmic dissipation and nanoparticle volume fraction etc., have been investigate their impact on profiles of nanofluid for velocity, temperature and concentration. Further, their effects on skin friction coefficient, Nusselt and Sherwood number are studied and discussed in details. The pre requisites of essential concepts have been involved in introduction section. The Lie group transformation and similarity transformation have been employed to altered the fundamental equations into similar dimensionless form and then after Runge-KuttaFehlberg scheme of fourth fifth order together with shooting technique is applied to solve them with the aid of standard MATLAB package. To check the validity of our code we have contrasted our results with those reported in previous literature. This investigation declared that boundary layer flow and heat transfer analysis may be performed in large industrial significance including industrial cooling applications as smart fluids, in nuclear reactors, automotive applications, electronic applications and biomedical applications. The MHD nanofluid flow in electrical conducting fluid can manage the rate of cooling and the required class of products can be obtained. The present study may support in the fields of applied science and also for the researchers working in the field of miniaturized technology, medical science and mechanical engineering etc.