Fuzzy linear regression models with absolute errors and optimum uncertainty

Shakouri, H.; Nadimi, Reza; Ghaderi, F.

doi:10.1109/ieem.2007.4419325

Cited by 12 publications

(5 citation statements)

References 15 publications

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“…Compared to traditional neural networks such as linear regression [15][16][17] and linear to nonlinear transformations [18] , CNN have two major advantages: local connections and weight sharing [19,20] . In traditional neural networks, all neurons in the network are connected, creating a high degree of interdependence between the input signal and all output results.…”

Section: Basic Principle Of Convolutional Neural Networkmentioning

confidence: 99%

Research on Cyst of Jaw Detection Algorithm Based on Alex Net Deep Learning Model

Guangyan,

Yanan,

Aihemaiti

et al. 2024

Preprint

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In clinical medicine, jawbone cysts are a common dental disease, and their symptoms are similar to other dental diseases, making diagnosis difficult. To address this issue, this paper proposes a cyst detection system based on Alex Net to achieve the detection of cysts on dental radiographs using a CBCT dataset. The system can detect potential cyst lesions and locations in a timely manner to assist doctors in diagnosis. The improved model achieves an average accuracy of 83.5% and a maximum accuracy of 99.9%, achieving a high cyst recognition rate on existing datasets. In addition, the extensive image enhancement techniques introduced in the Alex Net model also improve the performance of the model. The experimental results show that compared to Res Net and VGG Net, both networks are not ideal for the classification of jawbone cysts, and may not be able to effectively extract key features from medical images, resulting in low classification accuracy. Therefore, it is important to choose a suitable deep learning model for the diagnosis of specific dental diseases. In future research, it is possible to further explore how to combine multiple deep learning models to improve the accuracy of diagnosis of dental diseases such as jaw cysts. In addition, improving data preprocessing and enhancing techniques can further improve the generalization ability of the model. In summary, by combining deep learning and clinical medicine concepts and methods, more effective auxiliary diagnostic systems can be developed to improve the accuracy and efficiency of dental disease diagnosis.

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Section: Basic Principle Of Convolutional Neural Networkmentioning

confidence: 99%

Research on Cyst of Jaw Detection Algorithm Based on Alex Net Deep Learning Model

Guangyan,

Yanan,

Aihemaiti

et al. 2024

Preprint

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“…The government has developed AI for a variety of purposes, including transportation and reducing criminal risk. For instance, [53] uses artificial neural networks, a type of AI, to explore crime risk prediction as a factor that leads to safer travel in metropolitan settings. Using the database of the Chicago Police Department, the writers compiled crimes that occurred in the city of Chicago.…”

Section: Governancementioning

confidence: 99%

The AI vantage: an exposition of global dynamics

Kishor,

Patle,

Bhojane

2023

J. mechatron., artif. intell., eng.

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Over the past few years, there has been a growing interest in this field of Artificial Intelligence (AI). This review paper aims to examine the extent to which AI has been adopted across various domains in different regions of the world. Specifically, this study seeks to explore the effectiveness of AI in areas such as banking, governance, judiciary, and agriculture. While AI’s impact on these areas has been studied before, this research focuses on aspects that have not been given much needed attention so far. The study will begin by offering an overview of AI’s development from a regional perspective, analyzing 63 articles from leading journals and institutions to identify the most commonly used terminologies, theories, and technologies. The increasing computational power has played a crucial role in the advancement of AI. However, the role of AI in governance, judiciary, and legislature system has not been explored in depth in previous research. Furthermore, most studies tend to focus on single domain, whereas this paper aims to examine several domains and their relationship to AI. The study presents several AI-driven techniques, including Deep Neural Net (DNN), Artificial Neural Net (ANN), Candlestick Plots, Natural Language Processing (NLP), Explainable Deep Neural Net (xDNN), Attentional Maps, Digital Inventory, Deep Learning among others, that can be applied to enhance society’s performance in different domains. The research also delves deeper into the judiciary domain, proposing specific AI techniques that could be useful in this field. Additionally, tables summarizing different AI tactics relevant to each domain are presented.

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“…Linear Regression is a linear model, and commonly used type of predictive analysis in machine learning. Linear Model describes the connection between dependent variable and one or more independent variable(s) [13], [14].…”

Section: Linear Regressionmentioning

confidence: 99%

A Distinctive Approach on the Usage of Edge Computing Concept on Humidity Dataset through Regression Analysis

Sridhar¹,

Srinivas²

2022

IJCSMC

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Edge computing is a paradigm that can distribute the complexity of predictive analysis into smaller pieces, physically placed at the source of contextual information. This allows in processing large amounts of data where it is intricate to use a centralized cloud. Edge Computing makes this possible by taking control of data and services from central hubs, which reduces computational latency on servers. Humidity is one of the main factors that maintain the life of the surface. This article explains how to perform computational analysis at the "edge" by using humidity data sets, and also shows that the most modern data is sufficient for data analysis. Linear Regression and Random Forest Regression algorithms are utilized for data analysis. In addition, this article illustrates the importance of data series for predicting humidity by comparing the analysis of unshuffled data and shuffled data. Metrics have been used to assess the accuracy and point out the importance of sequential data feeds for analysis.

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Fuzzy linear regression models with absolute errors and optimum uncertainty

Cited by 12 publications

References 15 publications

Research on Cyst of Jaw Detection Algorithm Based on Alex Net Deep Learning Model

Research on Cyst of Jaw Detection Algorithm Based on Alex Net Deep Learning Model

The AI vantage: an exposition of global dynamics

A Distinctive Approach on the Usage of Edge Computing Concept on Humidity Dataset through Regression Analysis

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