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[PDF] Top 20 Statistics Model for Meteorological Forecasting Using Fuzzy Logic Model

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Statistics Model for Meteorological Forecasting Using Fuzzy Logic Model

Statistics Model for Meteorological Forecasting Using Fuzzy Logic Model

... Meteorological forecasting is one of the most essential and demanding operational tasks carried out by meteoric services all over the world (Guhathakurata, ...necessary. Forecasting the rainfall at ... See full document

6

Study of Load Forecasting Techniques using Fuzzy Logic

Study of Load Forecasting Techniques using Fuzzy Logic

... load forecasting for the ...models using the Fuzzy logic method without weather ...the forecasting models. In the study, two different fuzzy logic models (model 1 ... See full document

9

FORECASTING THE NUMBER OF DENGUE FEVER CASES IN MALANG REGENCY INDONESIA USING 
FUZZY INFERENCE SYSTEM MODELS

FORECASTING THE NUMBER OF DENGUE FEVER CASES IN MALANG REGENCY INDONESIA USING FUZZY INFERENCE SYSTEM MODELS

... the using of Fuzzy. Edangogade [10] applied Fuzzy in hydro_environment field and found that fuzzy approach good enough for the data history and more profitable than other statistical methods ... See full document

8

Electrical Load Forecasting Using Fuzzy System

Electrical Load Forecasting Using Fuzzy System

... work using ANN taking data from Duhok ELC (Control region of Iraq) of 2009 and ...generated using the models, where the output is found almost close to the actual ...load forecasting using ... See full document

11

Type-2 Fuzzy Logic Approach To Increase The Accuracy Of Software Development Effort Estimation

Type-2 Fuzzy Logic Approach To Increase The Accuracy Of Software Development Effort Estimation

... Recent statistics suggest the fact that work done in this area does not meet the needs of software ...efficient model for accuracy improvement and software effort estimation ...proposed model is ... See full document

8

Developing a Neuro Fuzzy Model for Weather Prediction

Developing a Neuro Fuzzy Model for Weather Prediction

... pure fuzzy logic based forecasting. In this study, a Neuro-fuzzy approach will be proposed to predict weather in Sadat region, western desert, ...proposed model uses a ... See full document

12

The Use of Fuzzy Logic Model to Investigate the Effect of Weather Parameter Impact on Electrical Load Based on Short Term Forecasting: Further Study

The Use of Fuzzy Logic Model to Investigate the Effect of Weather Parameter Impact on Electrical Load Based on Short Term Forecasting: Further Study

... Accurate load forecasting can enhance reliable or uninterrupted power supply to the customers. Usually, power supply starts from generation to transmission and finally to distribution, where consumers directly ... See full document

10

Development and Analysis of Standardized Precipitation Index, Reconnaissance Drought Index and Fuzzy Logic Drought Index for Sabarkantha, Gujarat

Development and Analysis of Standardized Precipitation Index, Reconnaissance Drought Index and Fuzzy Logic Drought Index for Sabarkantha, Gujarat

... Fuzzy Logic Drought Index (FLDI) Model 1 is prepared considering ‘Rainfall’, ‘Temperature’, and ‘Potential evapotranspiration’ as input variables and ‘Drought Index’ as an output ...first ... See full document

5

The fuzzy logic in air pollution forecasting ‎model

The fuzzy logic in air pollution forecasting ‎model

... The model presented in this paper predict the concentrations of ...This model of most models excels because of forecast pollution levels very depending stage time between data for select the number of hours ... See full document

7

Long Term Load Forecasting Using Fuzzy Logic Methodology

Long Term Load Forecasting Using Fuzzy Logic Methodology

... load forecasting model for medium/ long term power system ...including forecasting algorithms and the key variables (electrical and nonelectrical variables) that affect the demand forecasts were ... See full document

8

DETERMINATION OF PUPILS’ RETENTION ABILITY USING FUZZY LOGIC MODEL

DETERMINATION OF PUPILS’ RETENTION ABILITY USING FUZZY LOGIC MODEL

... A membership function (MF) is a curve that defines how each point in the input space is mapped to a membership value (or degree of membership) between 0 and 1 or as desired by the user. It also defines how each point in ... See full document

27

An Intelligent Air Traffic Control System using Fuzzy Logic Model

An Intelligent Air Traffic Control System using Fuzzy Logic Model

... Fuzzy logic is derived from fuzzy set theory. Fuzzy logic deals with approximate rather than precise ...precision. Fuzzy logic was developed for control operations to ... See full document

9

Online Full Text

Online Full Text

... the fuzzy numbers, such as accumulated generating operation, inverse accumulated generating operation, and matrix multiplication and inversion cannot be ...the fuzzy number series. In the paper, the ... See full document

9

DYNAMIC SENSOR RELOCATION TECHNIQUE BASED LIGHT WEIGHT INTEGRATED PROTOCOL FOR 
WSN

DYNAMIC SENSOR RELOCATION TECHNIQUE BASED LIGHT WEIGHT INTEGRATED PROTOCOL FOR WSN

... emulation model is developed using ACM, ACM trained FLC and ANFIS ...Simulink model is developed in the Matlab environment, simulations are performed & the results are ... See full document

8

A FUZZY LOGIC CONTROLLER FOR EMULATION OF SUITABLE INSULIN DOSE IN TYPE II DIABETIC PATIENTS

A FUZZY LOGIC CONTROLLER FOR EMULATION OF SUITABLE INSULIN DOSE IN TYPE II DIABETIC PATIENTS

... .This model is completely feasible, for example for a patient with 45 years old, blood pressure 13, BMI 25, FBS 135 and non -FBS 170 ,insulin dose will be ...our model regarding to this case was ... See full document

9

Adaptive Fuzzy Model Predictive Control for Non-minimum Phase and Uncertain Dynamical Nonlinear Systems

Adaptive Fuzzy Model Predictive Control for Non-minimum Phase and Uncertain Dynamical Nonlinear Systems

... is Model Predictive Control based on Fuzzy Logic, Genetic Algorithms or B&B, and Adaptive Control ...by using TS ...tuned using adaptive technique based on the error between the ... See full document

11

Development of Interest in Science and Interest in Teaching Elementary Science: Influence of Informal, School,  and Inquiry Methods Course Experiences

Development of Interest in Science and Interest in Teaching Elementary Science: Influence of Informal, School, and Inquiry Methods Course Experiences

... addition, using accuracy assumes the misclassification costs are equal for all data examples and it would not be necessarily realistic for some real-world applications such as medical diagnosis (Qin, ... See full document

127

A Model of Cellular Automata for the Fuzzy Control of Aphids

A Model of Cellular Automata for the Fuzzy Control of Aphids

... Volterra model allow us to propose rules that relate the variables of state to their own variations, that is, they come from the phase-plane of Lotka-Volterra ... See full document

9

Forecasting of River Sediment Amount using Machine Model

Forecasting of River Sediment Amount using Machine Model

... According to Table 1, when MAE, RMSE and R statistical criteria were compared, all models were good. All models are evaluated separately; GRNN (39.80 - 81.53 - 0.85) and SVM (24.38 – 55.61 – 0.90) models were found to ... See full document

7

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... Second fuzzy logic design. This shows the response of the second fuzzy logic when signals from error, error change and FLC1 are received and tasks carried out based on the fuzzy ...here ... See full document

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