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Disease Diagnosis System Using IoT Empowered with Fuzzy Inference System

Computers, Materials & Continua 2022年第3期70卷 5305-5319页

作者： Talha Mahboob Alam Kamran Shaukat Adel Khelifi Wasim Ahmad Khan Hafiz Muhammad Ehtisham Raza Muhammad Idrees Suhuai Luo Ibrahim A.Hameed Department of Computer Science and Information Technology Virtual University of PakistanLahorePakistan School of Information and Physical Sciences The University of NewcastleAustralia Department of Computer Science and Information Technology Abu Dhabi UniversityAbu DhabiUnited Arab Emirates School of Computer Science National College of Business Administration&EconomicsLahorePakistan Sir Syed College of Computer Science University of Engineering and TechnologyLahorePakistan Department of Data Science University of the PunjabLahorePakistan Department of ICT and Natural Sciences Norwegian University of Science and TechnologyTrondheimNorway

Disease diagnosis is a challenging task due to a large number of associated *** in the diagnosis process arises frominaccuracy in patient attributes,missing data,and limitation in the medical expert’s ability to define cause and effect relationships when there are multiple interrelated *** paper aims to demonstrate an integrated view of deploying smart disease diagnosis using the Internet of Things(IoT)empowered by the fuzzy inference system(FIS)to diagnose various *** Fuzzy Systemis one of the best systems to diagnose medical conditions because every disease diagnosis involves many uncertainties,and fuzzy logic is the best way to handle *** proposed system differentiates new cases provided symptoms of the ***,it becomes a time-sensitive task to discriminate symptomatic *** proposed system can track symptoms firmly to diagnose diseases through IoT and FIS smartly and *** coefficients have been employed to predict and compute the identified disease’s severity for each sign of *** study aims to differentiate and diagnose COVID-19,Typhoid,Malaria,and *** study used the FIS method to figure out the disease over the use of given data related to correlating with input *** tool is utilised for the implementation of *** procedure on the aforementioned given data presents that affectionate disease can derive from the *** results of our proposed method proved that FIS could be utilised for the diagnosis of other *** study may assist doctors,patients,medical practitioners,and other healthcare professionals in early diagnosis and better treat diseases.

关键词： Disease diagnosis system COVID-19 healthcare biomedical rules extraction

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Fast Matrix Computation Algorithms Based on Rough Attribute Vector Tree Method in RDSS

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Journal of Donghua University(English Edition) 2005年第4期22卷 72-78页

作者：文香军许晓鸣蔡云泽 Automation Department Shanghai Jiaotong UniversityShanghai 200030

The concepts of Rough Decision Support System (RDSS) and equivalence matrix are introduced in this paper. Based on a rough attribute vector tree (RAVT) method, two kinds of matrix computation algorithms — Recursive Matrix Computation (RMC) and Parallel Matrix Computation (PMC) are proposed for rules extraction, attributes reduction and data cleaning finished synchronously. The algorithms emphasize the practicability and efficiency of rules generation. A case study of PMC is analyzed, and a comparison experiment of RMC algorithm shows that it is feasible and efficient for data mining and knowledge-discovery in RDSS.

关键词： rules extraction matrix computation RMC PMC RDSS RAVT.

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An Improved WM Fuzzy Modeling Method for Blast Furnace Gas System

An Improved WM Fuzzy Modeling Method for Blast Furnace Gas S...

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第36届中国控制会议

作者： Yanwei Zhai Zheng Lv Ying Liu Jun Zhao Wei Wang School of Control Science and Engineering Dalian University of Technology

ISBN: (纸本)9781538629185

The blast furnace gas is an important secondary energy for the iron and steel *** an effective model to describe the state of BFG system is of great significant to maintain the system balance and *** the strong coupling characteristics of the blast furnace gas system and the high level noises in the industrial data,a simplex unscented kalman filter-based Wang-Mendel modeling method is proposed in this paper to improve the accuracy and generalization ability of the fuzzy *** the proposed method,the maximum posterior estimation of the center value in each fuzzy rule space is calculated in the probability density distribution perspectives by incorporating the kalman filtering method into rule extraction process,which eliminates the influence of noises effectively and improves the accuracy of the fuzzy *** experimental results by using the Lorenz time series with noises and the industrial data demonstrated that the proposed method could extract the fuzzy rules from the data accurately and had good performance for blast furnace gas system modeling.

关键词： Wang-Mendel fuzzy model simplex unscented kalman filter rules extraction blast furnace gas system

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Intersection Conditions Analysis Based On The Decision Tree

Intersection Conditions Analysis Based On The Decision Tree

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第36届中国控制会议

作者： Zhuang Liang Fenghua He Tianyu Zheng Control and Simulation Center Harbin Institute of Technology

ISBN: (纸本)9781538629185

This paper presents an analysis on intersection conditions that allow a flight vehicle to achieve the interception of a high-speed and maneuvering *** intersection conditions contain four parameters,including the intersection angle and initial distance and velocities of a fight vehicle and the ***,the relative motion model between a flight vehicle and the target with intersection angle is ***,intersection conditions analysis is conducted based on decision tree and relative rules are obtained from decision tree ***,Several simulations are conducted to prove the correctness and applicability of the rules.

关键词： Guidance Target maneuver Decision tree rules extraction

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Knowledge extraction Model for Power Load Characteristics of Special Days and Extreme Weather

Knowledge Extraction Model for Power Load Characteristics of...

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2009 IEEE International Conference on Intelligent Computing and Intelligent Systems(ICIS2009)

作者： Dou Quansheng School of Computer Science and Technology,Shandong Institute of Business and Technology,Yantai,China Shi Zhongzhi Institute of Computing Technology,Chinese Academy of Sciences,Beijing,China Pan Guanyu Department of Information Engineering,JiLin Business and Technology College,Changchun,China Yang Bin Heilongjing Electric Power Company Limited Harbin,China

Load forecasting is a traditional research field of power system,under normal circumstance,there are great similarities between the similar days,but under the condition of special days and extreme weather,load prediction has some *** model for load characteristics of special days and extreme weather was proposed in this paper,coding strategy and genetic operation of traditional genetic algorithm were redefined in the model,the relational rules about relation between power load special days and extreme weather were *** the same time,the credibility of these rules was proven by practice.

关键词： load forecasting rules extraction

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A new construction method of futures trading strategy construction based on AFS theory

A new construction method of futures trading strategy constr...

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第三十九届中国控制会议

作者： Yabing Du Xiaodong Liu Wenjuan Jia Mengmeng Liu School of Control Science and Engineering Faculty of Electronic Information and Electrical EngineeringDalian University of Technology

Futures trading is an advanced trading mode, which is developed from the spot trading and forward contract *** is a legal agreement between several people who don’t know each other to buy and sell goods at a specified time and at a predetermined price in the future. The asset they trade can be a commodity or financial instrument. How to obtain more income through futures investment is a central issue that many investors care and study. In recent years, many researchers have tried to apply artificial intelligence to futures trading and find High-yield and low-risk strategies on it. This paper proposes a method for constructing futures trading strategies based on inflection point analysis and axiomatic fuzzy set（AFS） theory. It can find the relationships between the Bollinger Bands of futures price data and the price differences by extracting association rules. And then the relationships will be basis of formulating the corresponding buying and selling strategies. The comparative experiments in virtual futures trading proves the practicability and superiority of the method with an ordinary fuzzy method of extracting association rules in virtual futures trading.

关键词： Futures Trading Axiomatic Fuzzy Set Theory rules extraction Inflection Point

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