[PDF] Top 20 Medium Term Load Forecasting using Adaptive Neuro Fuzzy Inference System
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Medium Term Load Forecasting using Adaptive Neuro Fuzzy Inference System
... of fuzzy logic and neural network approaches and naturally carries the advantages of ...future load, the historical load data from TATA POWER Company, Mumbai for complete one year 2013 is used to ... See full document
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Electricity Consumption Forecasting Using Adaptive Neuro Fuzzy Inference System (ANFIS)
... short-term load forecasting (STLF), medium-term load forecasting (MTLF) and long-term load forecasting ...forecasts load from one day or one ... See full document
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Flood Forecasting using Adaptive Neuro-Fuzzy Inference System (ANFIS)
... present study to develop ANFIS model, past discharge and rainfall data of study area are used to forecast flood in a river system. ANFIS models with various input structures and membership functions are ... See full document
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Short Term Electric Load Forecasting of 132/33KV Maiduguri Transmission Substation using Adaptive Neuro Fuzzy Inference System (ANFIS)
... The Adaptive Neuro-fuzzy based inference system (ANFIS) is applied to model the next hour load forecast for the 132/33kv Maiduguri substation using time of the day, day of ... See full document
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Voltage stability analysis of load buses in electric power system using adaptive neuro fuzzy inference system (ANFIS) and probabilistic neural network (PNN)
... Voltage stability margin (VSM) is defined as the distance between the normal/initial voltage operating point until the voltage critical/collapse point. VSM can be divided into two categories which are VSM for real power ... See full document
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Modelling tide prediction using linear model and adaptive neuro fuzzy inference system (ANFIS) in Semarang, Indonesia
... Semarang is becoming the center of some transportation facilities including Ahmad Yani airport, Tawang and Poncol train stations, also Terboyo bus station. Moreover, in the northern Semarang, there are a lot of ... See full document
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Survey of fuzzy inference model and impact on QOS parameters using adaptive neuro fuzzy inference system in MANET
... The properties of MANET include Neighbor Discovery, Data routing abilities, and limited wireless connectivity range and resource constraints. The important characteristic of MANET Distributed operation, multihop routing, ... See full document
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Load Frequency Controls of Three Are Interconnected Power System with Adaptive Neuro Fuzzy Inference System Approach Anil Kumar Obulasetty & Rami Reddy Ch
... The control objective is now to regulate the frequency of each area and to simultaneously regulate the tie-line power as per inter-area power contracts. As in the frequency, proportional plus integral controller will be ... See full document
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MULTI LEVEL GROUP KEY MANAGEMENT TECHNIQUE FOR MULTICAST SECURITY IN MANET
... type-2 fuzzy inference systems (IT2FIS) in short term load forecasting (STLF) on special ...type-2 fuzzy systems (IT2FSs) using Karnik Mendel ...the load values of ... See full document
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Voltage Stability Monitoring Using Adaptive Neuro-Fuzzy Inference System
... power system voltage ...power system and one at each particular bus as ...of system quantities needed to be measured and ...14-bus system and the results are ...applying load shedding ... See full document
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EFFICIENCY INCREASING FUNCTION FOR PMSM DR IVE USING ADAPTIVE FUZZY LOGIC CONTROLLER
... Gain Fuzzy Inference System (FTAGFIS) adaptive speed controller for the Permanent Magnet Synchronous Motor ...developed using Adaptive Neuro Fuzzy Inference ... See full document
12
Image Enhancement Using Adaptive Neuro-Fuzzy Inference System
... imaging system (sensor noise, limited system accuracy, finite precision, quantization of image data, ...imperfect medium between the original scene and the imaging system (random scattering, ... See full document
7
Solar Irradiance Prediction by a New Forecast Engine Composed Wavelet Packet Transform and Adaptive Neuro-Fuzzy Inference System
... short term prediction model based on wavelet packet transform and an adaptive neuro-fuzzy inference system with a high forecasting accuracy that depends on previous weekly ... See full document
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Rainfall Forecasting in Banyuwangi Using Adaptive Neuro Fuzzy Inference System
... However, the pattern can be shifted from the pattern predefined by previous studies. A study shows Indonesia is facing the challenge of climate change that is significant enough to alter the intensity of the rain and ... See full document
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Transformer’s Load Forecasting to Find the Transformer Usage Capacity with Adaptive Neuro-Fuzzy Inference System Method
... electric load forecasting using Adaptive Neuro-Fuzzy Inference System (ANFIS) method is better than Artificial Neural Network (ANN) method, this is indicated by ... See full document
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Wavelet Based short term load forecasting using optimized ANFIS
... on forecasting electric load consumption using optimized Adaptive Neuro-Fuzzy inference System ...variables using Daubechies 2 ...tested using weather ... See full document
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An Intelligent System For Forecasting Electric Load And Price
... Abstract—Electric load forecasting is an important research field to increase reliability of power supply and provide optimal load and minimum price scheduling in an intelligent ...short term ... See full document
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Diagnosis of Hepatitis using Adaptive Neuro Fuzzy Inference System (ANFIS)
... paper, Adaptive Neuro-Fuzzy Inference System (ANFIS) was employed to invoke neural network that provided structures for fuzzy inference engine (FIE) in order to learn ... See full document
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Preparation of flood susceptibility mapping using an ensemble of frequency ratio and adaptive neuro-fuzzy inference system models
... Natural disasters such as landslip, earthquakes, and floods annually cause a lot of financial and financial losses all over the world (Tierney et al., 2002). Floods are one of the natural disasters whose imposed damage ... See full document
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Electrical Load Forecasting Between 2015 and 2035 for Turkey Using Mathematical Modeling and Dynamic Programming
... In this study; between 2015 and 2035 years, amount of the total annual energy consumed and the amount of energy consumed in peak days were forecasted. TEIAS and TSI data are used between the years 1999-2014. The data ... See full document
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