This paper compares four different modeling techniques: Response Surface Method (RSM), Linear Radial Basis Functions (LRBF), Quadratic Radial Basis Functions (QRBF), and Artificial Neural Network (ANN). The models were tested by monitoring their performance in predicting the optimum operating conditions for Sesame seed oil extraction yields. Experimental data using three different solvents—hexane, chloroform, and acetone—with varying ratios of solvents to seeds, all under different temperatures, rotational speeds, and mixing times, were modeled by the three proposed techniques. Efficiency for model predictions was examined by monitoring error value performance indicators (R2, R2adj, and RMSE). Results showed that the applied modeling techniques gave good agreements with experimental data regardless of the efficiency of the solvents in oil extraction. On the other hand, the ANN model consistently performed more accurate predictions with all tested solvents under all different operating conditions. This consistency is demonstrated by the higher values of R2 and R2adj ratio equals to one and the very low value of error of RMSE (2.23 × 10−3 to 3.70 × 10−7), thus concluding that ANN possesses a universal ability to approximate nonlinear systems in comparison to other models.

Sustainability of agricultural practices depends on economic, environmental, and social conditions. The Rajasthan state of India has arid climatic conditions where kharif crops are commonly grown. In this work, the four major criteria are considered such as the farm area, crop yield per unit area, the cost prices, and the market sales price. Merged analytic hierarchy process (AHP) and entropy techniques have been employed to give reasonable weight coefficients for the objective and subjective weights to each criterion. Multiple attribute-based decision-making models (MADM) have been developed using three proven techniques, namely the Exprom2, the technique for order of preference by similarity to ideal solution (TOPSIS), and the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR). The crop Pennisetum glaucum emerged as the most productive kharif crop in the arid climatic conditions of Rajasthan, India under the given criteria. The sensitivity analysis of the three methods identifies the most significant criteria and validates that Pennisetum glaucum is the first ranked crop despite the interchange of the weights. The methodology used in this study may be applied across the globe to select appropriate crops for maximizing the profit, optimizing the natural resources, and promoting sustainable agricultural practices. This study may be used to enhance the agricultural gross domestic product (GDP) to make the agriculturalists self-sufficient and to help the state policymakers in making effective regional policies.

(Bi1–x La x )FeO3 (0.00 ≤ x ≤ 0.06) ceramics have been synthesized through a mixed oxide route to investigate their structural, morphological, optical, dielectric, and magnetic properties. All the samples are revealed to be in rhombohedral structures along with the R3c space group and 161 space group number. A high relative permittivity and the lowest tangent loss are observed in BLFO samples at the frequency range 1–100 MHz. The optical studies show that the excitation energy increases with the increasing La content. Moreover, the magnetization being strongly affected by crystallite size and microstrain has been investigated. The band gap energy increases with the increasing La content. The overall result of pure and doped La contents in BFO ceramics shows enhanced structural, dielectric, and optical properties.

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