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The purpose of this paper is to track the maximal power of wind energy conversion system (WECS) and enhance the search capability for WECS maximum power point tracking (MPPT).

The hybrid technique is the combination of tunicate swarm algorithm (TSA) and radial basis function neural network.

TSA gets input parameters from the rectifier outputs such as rectifier direct current (DC) voltage, DC current and time. From the input parameters, it enhances the reduced fault power of rectifier and generates training data set based on the MPPT conditions. The training data set is used in radial basis function. During the execution time, it produces the rectifier reference DC side voltage that is converted to control pulses of inverter switches.

Finally, the proposed method is executed in MATLAB/Simulink site, and the performance is compared with different existing methods like particle swarm optimization algorithm and hill climb searching technique. Then the output illustrates the performance of the proposed method and confirms its capability to solve issues.

The privacy of the information is a major challenge in the communication process. In the present modern generation, the cryptography plays a vital role in providing security for data, such as text, images and video while transmitting from source to destination through internet or intranet. The Rivest-Shamir-Adleman (RSA) is an asymmetric key cryptographic system, where the security of the method works on the strength of the key.

In an asymmetric key crypto system, a pair of keys is generated one public key for encryption and one private key for decryption. The major challenge of implementing the RSA is the power function which becomes tedious and time consuming as the exponential value increases. The Chinese remainder theorem proves to be the best for data encryption when it comes to execution time of the algorithm. The proposed novel RSA algorithm with lookup table (LUT) is an extension to the Chinese remainder algorithm, which works better for image and video in terms of time complexity.

This paper presents a LUT approach for implementing the RSA with a minimal processing time. The proposed algorithm was compared with the standard algorithms like, Chinese remainder theorem, binary approach and squared multiplication approach. As the size of the exponent value increases, the proposed method shows better performance compared to other standard methods.

This paper presents a LUT approach for implementing the RSA with a minimal processing time. The proposed algorithm was compared with the standard algorithms like, Chinese remainder theorem, binary approach and squared multiplication approach. As the size of the exponent value increases, the proposed method shows better performance compared to other standard methods.

Developing price forecasts for various agricultural commodities has long been a significant undertaking for a variety of agricultural market players. The weekly wholesale price of edible oil in the Chinese market over a ten-year period, from January 1, 2010 to January 3, 2020, is the forecasting issue we explore.

Using Bayesian optimisations and cross-validation, we study Gaussian process (GP) regressions for our forecasting needs.

The produced models delivered precise price predictions for the one-year period between January 4, 2019 and January 3, 2020, with an out-of-sample relative root mean square error of 5.0812%, a root mean square error (RMSEA) of 4.7324 and a mean absolute error (MAE) of 2.9382.

The projection’s output may be utilised as stand-alone technical predictions or in combination with other projections for policy research that involves making assessment.

Several chaotic system-based encryption techniques have been presented in recent years to protect digital images using cryptography. The challenges of key distribution and administration make symmetric encryption difficult. The purpose of this paper is to address these concerns, the novel hybrid partial differential elliptical Rubik’s cube algorithm is developed in this study as an asymmetric image encryption approach. This novel algorithm generates a random weighted matrix, and uses the masking method on image pixels with Rubik’s cube principle. Security analysis has been conducted, it enhances and increases the reliability of the proposed algorithm against a variety of attacks including statistical and differential attacks.

In this light, a differential elliptical model is designed with two phases for image encryption and decryption. A modified image is achieved by rotating and mixing intensities of rows and columns with a masking matrix derived from the key generation technique using a unique approach based on the elliptic curve and Rubik’s cube principle.

To evaluate the security level, the proposed algorithm is tested with statistical and differential attacks on a different set of test images with peak signal-to-noise ratio, unified average changed intensity and number of pixel change rate performance metrics. These results proved that the proposed image encryption method is completely reliable and enhances image security during transmission.

The elliptic curve–based encryption is hard to break by hackers and adding a Rubik’s cube principle makes it even more complex and nearly impossible to decode. The proposed method provides reduced key size.