GSA-based support vector neural network:a machine learning approach for crop prediction to provision sustainable farming

Purpose-Automated crop prediction is needed for the following reasons:First,agricultural yields were decided by a farmer’s ability to work in a certain field and with a particular crop previously.They were not always able to predict the crop and its yield solely on that idea alone.Second,seed firms frequently monitor how well new plant varieties would grow in certain settings.Third,predicting agricultural production is critical for solving emerging food security concerns,especially in the face of global climate change.Accurate production forecasts not only assist farmers inmaking informed economic andmanagement decisions but they also aid in the prevention of famine.This results in farming systems’efficiency and productivity gains,as well as reduced risk from environmental factors.Design/methodology/approach-This research paper proposes a machine learning technique for effective autonomous crop and yield prediction,which makes use of solution encoding to create solutions randomly,and then for every generated solution,fitness is evaluated to meet highest accuracy.Major focus of the proposed work is to optimize the weight parameter in the input data.The algorithm continues until the optimal agent or optimal weight is selected,which contributes to maximum accuracy in automated crop prediction.Findings-Performance of the proposed work is compared with different existing algorithms,such as Random Forest,support vector machine(SVM)and artificial neural network(ANN).The proposed method support vector neural network(SVNN)with gravitational search agent(GSA)is analysed based on different performance metrics,such as accuracy,sensitivity,specificity,CPU memory usage and training time,and maximum performance is determined.Research limitations/implications-Rather than real-time data collected by Internet of Things(IoT)devices,this research focuses solely on historical data;the proposed work does not impose IoT-based smart farming,which enhances the overall agriculture system by monitoring the field in real time.The present study only predicts the sort of crop to sow not crop production.Originality/value-The paper proposes a novel optimization algorithm,which is based on the law of gravity and mass interactions.The search agents in the proposed algorithm are a cluster of weights that interact with one another using Newtonian gravity and motion principles.A comparison was made between the suggested method and various existing strategies.The obtained results confirm the high-performance in solving diverse nonlinear functions.

Effect of asymmetrical wall heat flux and wall temperature ratio on mixed convection in a vertical micro-porous-channel with internal heat generation

Mixed convective heat transfer in a vertical parallel plate micro-porous channel with internal heat generation and viscous dissipation,varying wall heat flux ratio and wall tem­perature ratio at the boundaries is investigated using the Darcy-Brinkman model under local thermal non-equilibrium assumption.Numerical solution for both fluid and solid temperature distributions are obtained by applying the finite element method.The effect of pertinent param­eters such as Brinkman number,Rayleigh number,Darcy number,inter-phase heat transfer co­efficient,porosity scaled thermal conductivity ratio and solid internal heat generation are discussed.The results indicate that the Nusselt number increases with the increase in the solid internal heat generation as well as Rayleigh number in both wall heat flux ratio and wall tem­perature ratio boundary conditions.It is observed that with the quantitative increase in viscous dissipation parameter Br,Nusselt number Nu increases in the presence of internal heat gener­ation and it decreases in the absence of internal heat generation,for a specific range of values of wall heat flux ratio and wall temperature ratio.Beyond this range Nu increases with the increase in Dr regardless of internal heat generation.For the cases,constant wall temperature and wall heat flux ratios,good correlation is observed in the results obtained with that of available in the literature.