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Short-term electric load forecast is extremely important for the security management and cost control of the electric power industry, and thus it is of great significance to improve the forecast accuracy. Adaptive network-based fuzzy inference system (ANFIS) model, which combines the self-learning ability of neural network and the logical reasoning ability of fuzzy system, has some advantages in performance...
The status of any state of India depends significantly on various natural resources. The status may be developed, developing and under developed while natural resources may be climate, rivers flowing and the length of rainfall etc. In this paper, two natural resources such as number of rivers flowing and rainfall in that state have been taken at different times and their dependencies on the development...
This paper describes an applied approach using an Adaptive Neuro-Fuzzy Inference System to formulate the contents of novel diary functional food. In the development stage for a new functional food, it is required a careful balancing in the product ingredients in order to be achieved not only a healthily effect but an acceptable sensory properties. This imposes the solving of multiparametric task,...
Automated Essay Grading (AEG) systems that are currently available use different techniques to extract specific written dimensions features to assess the written prose. Several Neuro-Fuzzy approaches have been applied to try to solve the short essay AEG problem. The main idea behind this approach is to identify the number of main keywords (5 inputs) each of which has 4 synonyms based on specific constraints...
Precise control of electro-hydraulic actuator (EHA) system has been an interesting subject due to its nonlinearities and uncertainties characteristics. Good control can be designed when precise model of the system is available. ANFIS (Adaptive Neuro-Fuzzy Inference System) modeling technique has proven to be able to model various nonlinear systems. The objective of this paper is to obtain an ANFIS...
This paper describes the development of an inverse model for a direct current (DC) motor. The model consist of an Adaptive Network Fuzzy Inference System (ANFIS). The identification procedure includes: the experiment to collect data, ANFIS training and model validation in real-time. The obtained model is used to design a neuro-fuzzy inverse control strategy for trajectory tracking. The obtained real-time...
The lead time estimation is significant activity in each corporation that concerns with the breakdown of machines and maintenance. An integrated algorithm for forecasting weekly lead time based on Adaptive Neuro-Fuzzy Inference System (ANFIS) is proposed in this study. First, an ANFIS model is illustrated for the lead time forecasting simultaneously. The lowest Mean Absolute Percentage Error (MAPE)...
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