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The procedure and main result of a comparative study based on using an autoregressive model and an artificial intelligence technique applied to a Wimax traffic data series forecasting task are presented in this document. The time series forecasting methods being compared are: ANFIS model (Adaptive Network-based Fuzzy Inference Sys-tem) and ARIMA model (Auto-Regressive Integrated Moving Average). This...
The primary objective of steelmaking through Basic Oxygen Furnace (BOF) process is to achieve desired end point carbon content, temperature and percentage composition at the lowest cost and in the shortest possible time. As of now, most widely used models for prediction of parameters of converter steelmaking are mechanistic model, statistical model and neural network model for the prediction of the...
Product image form design, which focuses on customers' psychological demands, is arousing attention increasingly. This paper presents a novel approach of customer-oriented design for translating customers' kansei image into product design elements. The most influential form elements are identified through rough set theory. Based on this, the relationship between the key form elements and customers'...
Because of the strong non-linearity and uncertainty, the dynamics restraints of autopilots, as well as the effects of wave disturbances, designing a high performance ship course controller is always a difficult work. In order to solve the difficulty, an active disturbance rejection nonlinear control strategy is proposed, and the fuzzy controller is used to modify parameters of ADRC online which improve...
In this paper, the use of Adaptive Neural-Fuzzy Inference System (ANFIS) to study the design of Short-Term Load Forecasting (STLF) systems for the east of Iran was explored. This paper forecasts consumed load by using multi ANFIS. Entries of the presented model are into the multi ANFIS including the date of the day, temperature maximum and minimum, climate condition and the previous days consumed...
This paper presents an adaptive-network-based fuzzy inference system (ANFIS)-fuzzy data envelopment analysis (FDEA)) for long-term natural gas (NG) consumption forecasting and analysis. Six models are proposed to forecast annual NG demand. 104 ANFIS have been constructed and tested in order to find the best ANFIS for natural gas (NG) consumption. Two parameters have been considered in construction...
The increased utilization of flexible structure systems, such as flexible manipulators and flexible aircraft in various applications, has been motivated by the requirements of industrial automation in recent years. Robust optimal control of flexible structures with active feedback techniques requires accurate models of the base structure, and knowledge of uncertainties of these models. Such information...
A new tool for non-autonomous hierarchical systems modelling is proposed in this article. This tool is used for the modelling of monitoring functions and integrates the fuzzy logic in the temporal aspect of the events occurrence. The tool is also suited for the development of the hierarchical and distributed typologies structures and in modelling of recurrent functions. The proposed hierarchical systems...
In this paper we have applied the adaptive neuro-fuzzy inference system (ANFIS) which is realized by an appropriate combination of fuzzy systems and neural networks for forecasting a set of input and output data of Internet traffic time series. Several statistical criteria are applied to provide the effectiveness of this model. The obtained results demonstrate that the ANFIS model present a good precision...
In the wire bonding process, different combinations of parameter values will directly affect wire bonding quality. The optimal combination of these parameter values is very important to ensure the overall process quality response. Therefore, it is necessary to investigate the effects and interactive relationship of the bonding parameters on the bonding quality. This paper chooses the response factors...
This study tries to examine the impacts of emotional learning based fuzzy inference system (ELFIS) on completion time of projects. For the project management team, on time delivery within budget is a fundamental and important factor that highlights the importance of estimating the completion time of a project during its execution. This study implies four soft computing methods which are artificial...
In this paper, we developed a model based on the adaptive neuro-fuzzy inference systems (ANFIS) for analyzing a real non Gaussian process. The obtained results show that the generated values using ANFIS techniques have similar statistical characteristics as real data. Additionally, the developed model fits well real data and can be used for predicting purpose. Compared with existing model obtained...
Neural networks (NNs) have been widely used to predict financial distress because of their excellent performances of treating non-linear data with self-learning capability. However, the shortcoming of NNs is also significant due to a ldquoblack boxrdquo syndrome. Moreover, in many situations NNs more or less suffer from the slow convergence and occasionally involve in a local optimal solution, which...
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