In this paper, previous studies about Fuzzy regression had been presented. The fuzzy regression is a generalization of the traditional regression model that formulates a fuzzy environment's relationship to independent and dependent variables. All this can be introduced by non-parametric model, as well as a semi-parametric model. Moreover, results obtained from the previous studies and their conclusions were put forward in this context. So, we suggest a novel method of estimation via new weights instead of the old weights and introduce

Paper Type: Review article.

another suggestion based on artificial neural networks.

The integration of arti cial intelligence (AI), whether through devices or software, has become a critical tool in analyzing and evaluating technical performance. AI signi cantly contributes to enhancing athletic performance by enabling accurate data analysis and supporting educators in developing effective training programs and interactive curricula. This study addresses a noticeable gap in the literature regarding the attitudes and inclinations of educators toward AI in physical education and sport sciences—a gap often attributed to limited awareness and lack of access to moderntechnologies.Theprimaryaimofthestudyistoexaminethetendenciesandperceptionsoffemaleinstructorsin physical education and sport sciences toward the use of AI

This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n

The sound in the cinema and television occupies a large space in the level of use and expression. In addition to the functional aspect of the elements of the sound such as the dialogue, music, effects and silence, in shaping and supporting the narrative structure of the image in the dramatic work, it has today become and in light of the technical developments of the sound, an aesthetic value in the structure and formulation of the contents and ideas presented in the work. The sound also created a variety of forms before the work-factories in the artistic functioning, which enhances the emotional and expressive dimension of the image, and the researcher, as a result of many new developments in the expression o

            Requires economic work finding built institutional paint strategies and policies are formulated general economic and clarity in its stated objectives and the involvement of all economic institutions, political and stakeholders to discuss all the issues of economic, financial, monetary and analyzed for the purpose of renewal energies and determine the duties and responsibilities, leaving full freedom to the private sector in the formation of institutions to carry out his duties economic, and that the institutional structures to create the right climate for the implementation of its economic policies, which would facilitate the task of the private sector, and this h

Basically, this study aims to identify the extent to which Iraqi secondary school students use writing strategies and how proficiency level and students gender could affect writing strategy use. The study also examines the relationship between writing achievement and writing strategy use among Iraqi secondary school students. For this purpose, 140 Iraqi secondary school students were selected randomly from six different schools. Petric and Czarl’s questionnaire (2003) was adopted in the study as an instrument to collect the needed data. A software of SPSS used to analyze the collected data. The findings revealed that secondary school students appeared as low users of writing strategies; low proficient students do not show a sta

Physicians are likely to expend significant labor and time while manually calculating blood smears. Automatic computer-based methods for classifying acute lymphoblastic leukemia have trouble correctly lighting stained white blood cell microscopy images and accurately separating cells that touch or overlap. Additionally, incorporating machine learning techniques into medical services is very hard because doctors can deal with rough guesses as long as the results aren't too bad, but they can't use these calculations for actual medical care. Enabling a A deep network having knowledge of the accuracy of its own predictions is a fascinating and crucial issue. Most instances segmentation frameworks weigh the mask quality during the instance

It is important that real time stability in smart grids is ensured as the integration of renewables and the complexity of the systems grows. In this paper, we provide a solid architecture, which combines a Residual CNNLSTM deep neural network predictor, FPGA-accelerated Model Predictive Control (MPC), and SHAP-based explainability. The proposed method predicted with 99.8% accuracy using the Electrical grid Stability Simulated Dataset (UCI) and minimized the instability rates surpassing 85 percent in all operating conditions. Meeting real-time operating needs, FPGA deployment on a Xilinx Zynq UltraScale+ provided 3.1 ms latency and 5 times reduced energy consumption against CPU processing. By emphasizing bus voltage and frequency as major in