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Estimation of solar radiation is considered as the most important parameter for the design and development of various solar energy systems. But, the availability of the required data is very scarce and often not readily accessible. The foremost objective of the present study was to estimate the monthly average global solar radiation (GSR) at various locations for China province, by the generalized...
This paper addresses optimization in cutting parameters to obtain minimum surface roughness using multiple metamodeling techniques like Design of Experiments (DOE), Response Surface Methodology (RSM) and Fuzzy inference system. The second order mathematical models in terms of machining parameters were developed for surface roughness prediction using RSM on the basis of experimental results. The model...
The purpose of the study was to determine the applicability of the SERVPERF model in the Indian Banking Sector and also determine, if any, the differences in the service quality perception of service performance, customer satisfaction and purchase intention between public and co-operative retail banking units. The findings confirm that the SERVPERF dimensions of Tangibility, Reliability and Responsiveness...
The objective of this paper is to develop a Model Predictive Control (MPC) for a Shell and Tube Heat Exchanger. Since the heat exchanger is a highly non linear system, the operating zone of the system is divided into different zones. For each zone, a model is developed. Even though PID controllers are widely used for the control of heat exchangers, there is still a need for optimizing and conservation...
This paper analyzes and predicts the Average Global Temperature time series data. Three different variants of ARIMA models: Basic ARIMA, Trend based ARIMA and Wavelet based ARIMA have been used to predict the average global temperature. Out of all the three linear models, it has been observed that Trend based ARIMA method outperforms basic ARIMA method and Wavelet based ARIMA method outperforms Trend...
Azeotropic distillation is a special case of multicomponent distillation used for separation of binary mixtures which are either difficult or impossible to separate by ordinary fractionation. It is commonly used to separate close boiling mixtures with far fewer trays than in conventional distillation and with less circulation, resulting in lower equipment and energy costs. It is widely used for the...
Conical tank level process was studied experimentally to obtain the process model. The linear portion of this non linear model was considered and different control schemes such as discrete time Proportional Integral Derivative control (DTPID) and Discrete time Model Predictive Control (MPC) were implemented in MATLAB environment. Among these two control schemes, MPC resulted with minimum rise time,...
This study deals with the development of a surface roughness prediction model for machining EN-31 steel alloys using multiple regression and artificial neural networks . The experiments have been conducted using composite factorial design of experiments on heavy duty lathe turning machine with tungsten carbide cutting tools. A second order multiple regression model in terms of machining parameters...
Mechanical component design by safety factors using nominal values without considering uncertainties may lead to designs that are unsafe, or too conservative and thus not efficient. Design of a helical compression spring is one of complex and time consuming design procedure. This paper presents development of mathematical models to predict the outer diameter of a typical helical spring. This paper...
Effective utilization of computing resources and prediction of future resource capabilities are needed to achieve high performance computing in grid Environment. To ensure this, effective and flexible forecasting and prediction method needed to use time-shared resources for large applications which impact greater importance for scheduling. Predicting the available performance on each resource is basic...
To advance the state of the art in developing the protocols for Ubiquitous Underwater Acoustic Sensor Networks (UU-ASN) relies on the use of computer simulations to evaluate protocol performance. To simplify the complexity in implementation, physical environment characteristics are not implemented in detail in simulation ensuring a logical simulation runtime performance. Understanding the subject...
Business intelligence is an effective technology to take right decisions at right time for the survival of any business. Business intelligence can be applied to all kind decision making and prediction analysis. Business performance can be identified by using bankruptcy prediction. In this research we are developing a business intelligence model to predict the business performance by using bankruptcy...
An experimental study was conducted on a laboratory scale humidity system to obtain the empirical model (process). A pseudo random sequence was introduced for the obtained model to get the input and output data. Different models such as autoregressive exogenous input model (ARX), non linear ARX and a feed forward neural network (FNB) model using back propagation algorithm were tried in MATLAB environment...
In this paper a novel prediction scheme is proposed to efficiently predict the long range exchange rates using Radial Basis Function Neural Network(RBFNN). These models have been employed to predict currency exchange rate between 1 US$ to Indian Rupees and Japanese Yen. The performance of the RBF models is evaluated through simulation study and the results have been compared with Multilayer Layer...
The study of Quality of Service (QoS) and the extent of resource utilization are the two major components of Cloud Computing. The accurate modelling and simulation of flow of processes in cloud environment is an essential part of service level architecture. In this paper, an analytical model has been developed for identifying the pattern of inter-arrival processes and the service of processes. Empirical...
Weather prediction is an ever challenging area of investigation for scientists. In this paper the application of artificial neural networks to predict the weather of Bhopal city has been proposed. The weather parameters like maximum temperature, minimum temperature and relative humidity etc. has been predicted. When performing predictive modeling the key criteria is always accuracy. We are trying...
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