neuro-fuzzy data analysis
Analysis of Control of Inverted Pendulum using Adaptive Neuro Fuzzy system
... Fuzzy logic controller for Inverted Pendulum: It can be built into anything from small, hand-held products to large computerized process control systems. It uses an imprecise but very descriptive language to deal ...
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A novel optimal medium resolution remote sensing image classification using Neuro fuzzy approach
... sensing data is becoming richer, how to extract meaningful surface information from the emote sensing data has become a problem pressed for ...statistical analysis of pixel brightness, however, due ...
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Comparative Analysis Of Neuro-Fuzzy Model For Human Resources
... Neuro Fuzzy designs focus on specific observations and enhance the effectiveness rating of decision ...Moreover, Neuro Fuzzy design doesn't call for a priori knowledge of weights for inputs ...
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Vol 12, No 1 (2014)
... component analysis (PCA) was proposed and comparison of image fusion with different techniques based on fusion quality performance metrics is ...crisp, Fuzzy logic and Neuro- Fuzzy logic are ...
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Classification of MRI Brain Images Using Neuro Fuzzy Model
... compared with the test sample feature obtained and classified as one of the extracted character. [2] The feature extraction is done using principal component analysis (PCA).This technique is mostly used for the ...
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A Review Of Clinical Data Prediction Using Different Data Mining Technique And Neuro Fuzzy System
... ANN has absolutely settled itself as the most effectively displaying system for biomedical applications, especially in the range of example acknowledgment. Throughout the years, a few sorts of ANN have been produced, ...
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Analysis and Design of a Self-Tuned Neuro-Fuzzy Based IM Drives
... a Neuro- Fuzzy controller (NFC), as an AIC, is considered because of limitations of either fuzzy logic or neural ...simple fuzzy controller implemented in the motor drive speed control has a ...
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A Comparative Analysis of Computer Based Forecasting Models Used In Stock Exchange Prediction
... comparative analysis of the use of these models in stock exchange ...used data for the period between January 2010 to December 2015, and used each of The Markov model, Neuro-fuzzy system, ...
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Predict the Inverse Kinematic Solution to Manipulate Duplicate Using Anfis
... and analysis of inverse kinematics 1 DOF 5 O7- We suggest duplicate DOF ...used Neuro System Fuzzy Inference) to the data that has been created to solve the inverse kinematics ...proposed ...
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A neuro-fuzzy approach to the reliable recognition of electric earthquake precursors
... the neuro-fuzzy model is a result of a hybrid algorithm, a combination of the least squares es- timator and the error back-propagation ...the fuzzy inference ...the fuzzy inference ...
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Surge Detection System Using Gaussian Curve Membership Function
... Neural fuzzy. Results: By testing the new Neural- Fuzzy system which has been created for demonstrate the validity of proposed control scheme, the new neural-fuzzy system get a good results compared ...
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Performance Evaluation of CFRP Reinforced Concrete Members Utilizing Fuzzy Technique
... Network-based Fuzzy Inference Sys- tem (ANFIS) having mixed learning rules (Cao et ...the neuro-fuzzy system used in this study. The neuro-fuzzy system comprises 5 Layers: Layer 1 is ...
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Optimization of functional Spirulina cookies on their sensory attributes
... advanced Neuro- Fuzzy ...Adaptive Neuro-Fuzzy Inference System (ANFIS) called ...adaptive Neuro fuzzy inference system (CANFIS) which can send multi control signals to the ...
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Electricity Consumption Forecasting Using Adaptive Neuro Fuzzy Inference System (ANFIS)
... Research in [13] applied pre-processing to improve noisy and missing data. They then considered the time of day, the day of the week, the heating degree of the day (HDD) and cooling degree of the day (CDD) as ...
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Utilization of new computational intelligence methods to estimate daily Evapotranspiration of wheat using Gamma pre processing
... First, the normalization on the data is done in line with the following expression. There are two main advantages to normalize features before applying AI methods for prediction. One advantage is to avoid using ...
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Type-2 Fuzzy Logic Approach To Increase The Accuracy Of Software Development Effort Estimation
... type-2 fuzzy logic. In order to teach type-2 fuzzy logic, the gradient descent method and the neuro-fuzzy-genetic hybrid approach have been ...
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DEVELOPMENT AND APPLICATION OF A STAGE GATE PROCESS TO REDUCE THE UNERLYING RISKS OF IT SERVICE PROJECTS
... of fuzzy logic and artificial neural ...the fuzzy systems (human- like reasoning style) with the learning and connectionist structure of neural ...of Neuro-Fuzzy system is its universal ...
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The Most General Intelligent Architectures of the Hybrid Neuro-Fuzzy Models
... numerical and linguistic knowledges. The hybrid neuro-fuzzy architectures, are reflected a strong structure when the prediction of the input-output is obtained. Meanwhile, they don’t require analytical ...
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Threshold Neuro Fuzzy Expert System for Diagnosis of Breast Cancer
... designed to standardize reporting, and is used by radiologists, medical professionals to communicate a patient's risk of developing breast cancer. This indicates the radiologist's opinion of the absence or presence of ...
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Neuro Fuzzy approach for the predictions of economic crisis
... Neuro-Fuzzy approach for the predictions of economic crisis Giovanis, Eleftherios.[r] ...
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