Prediction of well-grounded market information, particularly short-term forecast of prices of agricultural commodities, is the essential requirement for the sustainable development of the farming community. Such predictions are mostly performed with the help of time series models. In this study, the soft computing method is used for short-term forecasting of agriculture commodity price based on time series data using the artificial neural network (ANN). The time series data for sunflower seed and soybean seed are considered as the agriculture commodities. The soybean seed time series data were collected for the period of five years (Jan 2014–Dec 2018), for Akola district market, Maharashtra, India. The sunflower time series data were collected for the period of six years (Jan 2011–Dec 2016), for Kadari district market, Andhra Pradesh, India. The dataset is available at the Indian government website taken from the website www.data.gov.in. For forecasting, the ANN model is used on the abovementioned datasets. The performance of the model is compared with the result of the traditional ARIMA model. The mean absolute percentage error (MAPE) and root mean square percentage error (RMSPE) are considered as the performance parameters for the forecasting model. It is observed that the ANN is a better forecasting model than the ARIMA model by considering the two forecasting performance parameters MAPE and RMSPE.

Laminated composite plates are inevitable parts of structure due to its superior properties than that of conventional material. Many times, these structural elements are subjected to the partial loadings during various applications which arises buckling in the elements. This necessitates proper analysis of these types of structural member for better safety and stability. In the present paper buckling analysis of laminated composite stiffened plate under in-plane localized edge loading is presented. Buckling load for various cases of partial edge loading are investigated for different fiber orientations and loading extent. Finite element method-based MATLAB program is developed for the present analysis. Validation study is done, which shows well agreement with the results already published.

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Laminated composite plates are well known structural member since last four decades because of its high stiffness and strength to weight ratio. Usually this type of structural members is subjected to partial biaxial loading during their functioning. For better safety and stability of structure, analysis of these structural member in that condition of loading is necessary. In this present analysis buckling response of laminated composite plates under biaxial partial in-plane loading is examined and effect of various parameters like aspect ratio, stacking sequence, fiber orientation and plate thickness ratio of nondimensionalised critical buckling load (NCBL) are revealed. A MATLAB program is developed higher order shear deformation theory based on finite element method for buckling analysis of laminated composite plate. Efficiency of the program is checked by comparing the result of the present work with that of already published which shows good favour of later one.