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Wheat is the main growing cereal crop in India. For the country, designing, estimating productivity is the important tool for predicting the production of wheat to determine the circumstances that would be the value of production upcoming year. Fuzzy time series deals with the problems associated with unpredictability ambiguousness and cloudiness. In this study enlargement of fuzzy time series variant model is used in forecasting wheat production. The data of previous years from 2000 to 2021 was taken for analysis and the proposed method on fuzzy time series estimates future events' precision rate. The suggested method used the percentage change as the Universe of Discourse and Average-based Partitioning. [ABSTRACT FROM AUTHOR]

One of the popular method for prediction of medical related data is Binary Logistic Regression. This method helps in understanding the relation between the independent variables and the dependent variable and to explore the relationship between them. The aim of this paper is to build a binary logistic model by identifying the various factors that trigger the heart disease of a person.The various factors influencing the heart disease of a person was computed and the performance of this method were evaluated based on standard statistical measures such as MAE, MAPE, RMSE, etc. The results obtained shows that BLR model can be used to monitor the heart disease conditions satisfactorily. [ABSTRACT FROM AUTHOR]

In this paper ,Autocorrelation (ACF) and Partial autocorrelation (PACF) functions had been envisioned to help in identifying appropriate orders of the Autoregressive model of order p (AR) and Moving Average model of order q (MA). The Bayesian Information Criteria (BIC) test was done on numerous models and it was found the model ARIMA (1, 1, 0) has the least BIC value. Ljung Q statistics data showed that there was no serial correlation across all the models. The standard error measures such as MSE, MAE, MAPE was calculated for the forecasting rates and was found to be minimal. [ABSTRACT FROM AUTHOR]

This paper brings out a contrast among Networking Model, Auto Regressive Moving Average Model, combinational models of ANN and ARIMA in forecasting the future exchange prices for US Dollar (USD) / Indian Rupees (INR). Simulation effects of combination models were taken in comparision with outcomes of ANN based ARIMA based models. Experimental results reveal that hybrid version of ANN and ARIMA can closely forecast the foreign exchange marketplace. [ABSTRACT FROM AUTHOR]

The authors introduced the concept of generalized semiclosed sets and generalized semiopen sets in topology. Later R.Devi[4] et al have defined and studied the concept of generalized semiopen functions and generalized semiclosed functions in between topological spaces. The aim of this paper is to introduce a new class of functions called fuzzy contra generalized semiopen functions using generalized semiopen functions. We also define and study the class of functions called fuzzy pgs open, fuzzy contra pgs open, fuzzy always contra pgs open and their basic characterizations. [ABSTRACT FROM AUTHOR]

Driver rest is one of the main sources of mishaps and passing for some individuals and the economy. As of late, specialists have started to perceive that lack of sleep is a positive, industry-driving reaction. In this article, we suggest including CNN-based savvy glasses for eye acknowledgment and rest estimation. This new response is contrasted with the customary technique in view of the strategy for comprehension. Both execution, battery utilization, and impression are assessed for execution in incorporated glass. The outcomes show that CNN has over 7% of the precision found at the algorithmic level. Moreover, migraines in memory and battery duration are genuine and make CNN a potential answer for sleep deprivation. [ABSTRACT FROM AUTHOR]

Neural organizations are probably the most intelligent technique for information mining involved by analysts in different fields throughout the last ten years. Securities exchange gauges and examination play had a critical influence in the present economy. The different calculations utilized in arranging can be delegated (AR, MA, ARIMA, ARMA) and nonlinear models. Here we utilize two different financial exchange shutting dates the Indian Stock Exchange (NSE) and the New York Stock Exchange. The pipeline was prepared on the securities exchange of one NSE organization and anticipated five unique organizations in the NSE and NYSE. CNN has shown that it is the best model. The channel was ready with NSE data; however, it was feasible to anticipate the NYSE. This was conceivable in light of the fact that both financial exchanges share inner qualities. Contrasting the outcomes and the ARIMA model, it was observed that the muscle strands were more than typical. [ABSTRACT FROM AUTHOR]

Significant progress has been made in the field of lung cancer over the years (chemical rehabilitation, radiotherapy, individualized treatment). Nevertheless, lung cancer remains a threat to society and a leading cause of death for thousands of people worldwide. The subject of this paper is the diagnosis of lung cancer. Lung cancer is diagnosed using computerized tomography (CT) scans. To accurately diagnose lung cancer, different algorithms are used. The image is filtered through a sharp hidden filter in this case. The edges and areas of the cancer are detected using a flexible canvas method. To identify the features andpredict the risk of lung cancer, using the neural network. The K-Nearest Neighbors method is used to separate cancerand lungs. Lung cancer is diagnosed using computerized tomography (CT) scans. To accurately diagnose lung cancer, different algorithms are used. The image is filtered through a sharp hidden filter in this case. The edges and areas of the cancer are detected using a flexible canvas method. To identify the features and predict the risk of the Using a neural network to study lung cancer. The K-Nearest Neighbors method is used to separate cancer and lungs. Lung cancer has been growing in recent years, so it is very important to know if tumor has turned into cancer. Prognosis occurs early and Accurate predictions can save many lives and assist doctors in starting therapy. CT (computed tomography) is a type of imaging that uses a is important in determining the condition of a plant by determining its size, location, and other factors. [ABSTRACT FROM AUTHOR]

Coronavirus disease of 2019 (COVID-19) has become widespread within few months and it has lead to a dramatic loss for human life worldwide. This pandemic impacts tens of millions of deaths each day and the number of people were dead by covid-19 is gradually increasing throughout the globe. During this pandemic situation control, we tend to propose a future prediction using Machine Learning algorithms on the death rate, the number of recovered estimates and the number of daily confirmed COVID-19 cases reported within the next ten days. It is based on Machine Learning technique. This forecasting method will predict the upcoming number of COVID-19 cases. Here we use four standard models for forecasting includes linear Regression (LR), The Lowest Absolute and Selective Shrinking Operator (LASSO), Vector Assistance (SVM) and exponential smoothing (ES) will predict the number of COVID-19 cases in future. These four models make three predictions: the mortality rates, the number of newly affected COVID-19 cases and the cummulative number of recovered cases in the next 10 days. These methods are better used in the COVID-19 situation. Based upon the findings, it is a encouraging method to use these standard models in the current situation of COVID-19 spread. The analysis shows that among all the standard forecasting models, ES model performs best, then LR and LASSO which also performs well in predicting the new infected cases of corona, death rate and recovery cases. Whereas the results of SVM were very bad in all the prediction scenarios from the given covid-19 data set. The predictions made by these models relating to the current situation are accurate and will also be useful for future awareness of the future situation. This paper will be enhanced continuously and next we are planning to traverse the prediction methodology using the updated covid-19 data set and we will make use of the most precise and best Machine Learning models for forecasting in future. [ABSTRACT FROM AUTHOR]

The solution of the problem obtained using Homotopy Perturbation Method (HPM) in this paper. Considered the boundary layer fluid flow over porous medium with chemical reactions and heat transfer. Using Similarity variables in non-linear PDE it will be reduced to ordinary DE then the solution found using HPM. The fluid flow features and the different values of governing parameters are analysed using graphs. [ABSTRACT FROM AUTHOR]

Soret and Dufour effect with hall current of a magneto hydro dynamic flow of a viscous fluid through vertical porous channel is studied here. Also studied the impacts of ramped wall temperature on the incompressible fluid. Using regular perturbation technique with boundary conditions the velocity, temperature and concentration of the fluid are calculated and it shows the velocity of the fluid increases when Soret number increases and velocity decreases with the increasing values of Dufour number. Also the variations in temperature and concentration also studied with the help of graphs. [ABSTRACT FROM AUTHOR]

From this paper analyses about mass and heat mass transfer effects along by thermal diffusion along with warm source of an oscillatory flow in a 2D, thick, electrically fluid through an infinite vertical penetrable plate with moving condition within a flooded porous medium into the occurrence of transfer attractive field and chemical reaction. Heat source and soret impacts are added into the governing equation to discuss about the velocity, temperature and concentration profile of the current problem. The series expansion method is used to get the analytical solution and the relevant results are depicted through graphs. Various non-dimensional parameters like Chemical response parameter, Prandtl number, Soret effect, magnetic field parameter and Grashof number for mass transfer are all discussed through graphs. [ABSTRACT FROM AUTHOR]

The aim of the present paper is to explore radiation effect with heat source on unstable natural convective MHD flow past on vertical porous plate. In perpendicular direction to the plate an uniform magnetic field will be applied. Thermal radiation effect, chemical reaction effect and soret effect are included. Reactions of various parameters on velocity, temperature and concentration are verified and analyzed through graphs. [ABSTRACT FROM AUTHOR]

In this paper we have studied Chemical Reaction of free convective MHD flow through vertical porous plate with variable temperature through a porous medium with heat and mass transfer. Considered the vertical plate and the medium of flow are porous. The effects of the physical parameters on the velocity, temperature, concentration, skin friction, Nusselt number have been analyzed through graphs and tables. The present study has great significance in different field of science and engineering. These flows appear in a wide variety of industrial applications and chemical process industries. [ABSTRACT FROM AUTHOR]

This present paper investigates the impact of radiation on liquid stream and warmth and mass exchange over a vertically swaying permeable level plate installed in permeable medium with wavering surface temperature. Mass transfer effects are added into the governing equations. The analytic solutions of the velocity, temperature and concentration profiles are obtained. The effect of physical parameters Prandtl number Pr, Grashof number Gr, Suction parameter S, Magnetic parameter, Darcy number and radiation parameter R, Schmidt number Sc, Modified Grshof number Gc on the velocity, temperature and concentration profiles are analysed and the results are depicted through graph. [ABSTRACT FROM AUTHOR]

This paper deals with the combined effect mass transfer and sorect effect for the oscillatory flow in the transverse attractive field and radiative warmth exchange to shaky stream of a directing optically dainty liquid through a channel recorded with immersed permeable medium and non-uniform dividers temperature. The thermal diffusion and mass transfer effects are added into the governing equations and the results are obtained through petribution technique. Various parameters like Grashof number, Modified Grashof number, Magnetic parameter, Radiation parameter, Peclet number, Darcy number, Heat source parameter, Chemical reaction parameter, Porous medium parameter, Schmidt number, Thermal diffusion parameter are all discussed, and results are analyzed by s graphs for velocity temperature and concentration profiles. The rate of skin friction and Nusselt number are also discussed. [ABSTRACT FROM AUTHOR]