SEDA KARATEKE

Makale | 2022 | Arabian Journal of Mathematics

Here, we present multivariate quantitative approximations of Banach space valued continuous multivariate functions on a box or RN , N ∈ N, by the multivariate normalized, quasi-interpolation, Kantorovichtype and quadrature-type neural network operators. We examine also the case of approximation by iterated operators of the last four types. These approximations are achieved by establishing multidimensional Jackson type inequalities involving the multivariate modulus of continuity of the engaged function or its high-order Fréchet derivatives. Our multivariate operators are defined using a multidimensional density function induced by t . . .he Richards’s curve, which is a generalized logistic function. The approximations are pointwise, uniform and L p. The related feed-forward neural network is with one hidden layer Daha fazlası Daha az

Javad Rahebi

Makale | 2023 | Springer

Compressing the image causes less memory to be used to store the images. Compressing images increases the transmission speed of compressed images in the network. Vector quantization (VQ) is one of the image compression methods. The challenge of the vector quantization method for compression is the non-optimization of the codebooks. Codebook optimization increases the quality of compressed images and reduces the volume of compressed images. Various methods of swarm intelligence and meta-heuristics are used to improve the vector quantization algorithm, but using meta-heuristic methods based on mathematical sciences has less history. T . . .his paper uses an improved sine–cosine algorithm (SCA) version to optimize the vector quantization algorithm and reduce the compression error. The reason for using the SCA algorithm in image compression is the balance between the search for exploration and exploitation search by sine and cosine functions, which makes it less likely to get caught in local optima. The proposed method to reduce the calculation error of the SCA algorithm uses spiral trigonometric functions and a new mathematical helix. The proposed method searches for optimal solutions with spiral and snail searches, increasing the chances of finding more optimal solutions. The proposed method aims to find a more optimal codebook by the improved version of SCA in the VQ compression algorithm. The advantage of the proposed method is finding optimal codebooks and increasing the quality of compressed images. The proposed method implementing in MATLAB software, and experiments showed that the proposed method’s PSNR index improves the VQ algorithm’s ratio by 13.73%. Evaluations show that the proposed method’s PSNR index of compressed images is higher and better than PBM, CS-LBG, FA-LBG, BA-LBG, HBMO-LBG, QPSO-LBG, and PSO-LBG. The result shows that the proposed method (or ISCA-LBG) has less time complexity than HHO and WOA compression algorithms.Compressing the image causes less memory to be used to store the images. Compressing images increases the transmission speed of compressed images in the network. Vector quantization (VQ) is one of the image compression methods. The challenge of the vector quantization method for compression is the non-optimization of the codebooks. Codebook optimization increases the quality of compressed images and reduces the volume of compressed images. Various methods of swarm intelligence and meta-heuristics are used to improve the vector quantization algorithm, but using meta-heuristic methods based on mathematical sciences has less history. This paper uses an improved sine–cosine algorithm (SCA) version to optimize the vector quantization algorithm and reduce the compression error. The reason for using the SCA algorithm in image compression is the balance between the search for exploration and exploitation search by sine and cosine functions, which makes it less likely to get caught in local optima. The proposed method to reduce the calculation error of the SCA algorithm uses spiral trigonometric functions and a new mathematical helix. The proposed method searches for optimal solutions with spiral and snail searches, increasing the chances of finding more optimal solutions. The proposed method aims to find a more optimal codebook by the improved version of SCA in the VQ compression algorithm. The advantage of the proposed method is finding optimal codebooks and increasing the quality of compressed images. The proposed method implementing in MATLAB software, and experiments showed that the proposed method’s PSNR index improves the VQ algorithm’s ratio by 13.73%. Evaluations show that the proposed method’s PSNR index of compressed images is higher and better than PBM, CS-LBG, FA-LBG, BA-LBG, HBMO-LBG, QPSO-LBG, and PSO-LBG. The result shows that the proposed method (or ISCA-LBG) has less time complexity than HHO and WOA compression algorithms Daha fazlası Daha az

FATMA ALTUNTAŞ

Makale | 2023 | Springer

Renewable energy management is critical for obtaining a significant number of practical benefits. Wind energy is one of the most important sources of renewable energy. It is extremely valuable to manage this type of energy well and monitor its development. Data-driven analysis of wind energy technology provides essential clues for energy management. Patent documents are extensively used to follow technology development and find exciting patterns. Patent analysis is an excellent way to conduct a data-driven analysis of the technology under concern. This study aims to define concepts related to wind energy technologies and cluster the . . .se concepts to manage wind energy well in practice. Although many efforts have been made in the literature on wind energy, no study defines the concepts related to wind energy technologies and clusters these concepts. This study proposes a text mining and clustering-based patent analysis approach to overcome the limitations of previous studies. Data-driven analysis collects and assesses patent documents related to wind energy technologies. Patent documents are collected from the United States Patent and Trademark Office. Text mining is applied to the abstracts of patent documents, and the k-means clustering algorithm is utilized to determine the distribution of the keywords among the clusters. The results of this study show that the contents of the patent documents are mostly related to the tower, and the propeller blades placed at the top of the tower should rotate smoothly with the wind speed for better energy production Daha fazlası Daha az