[PDF] Top 20 Evaluation of Artificial Neural Networks in Foreign Exchange Forecasting
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Evaluation of Artificial Neural Networks in Foreign Exchange Forecasting
... and forecasting of exchange rates of four countries (Great Britain Pound, Japanese Yen, Nigerian Naira and Batswana Pula) using Artificial Neural Network, the objective of this paper is to use ... See full document
8
Prediction of Stock Prices Using Artificial N...
... risk evaluation, speech recognition, monitoring, marketing, character recognition, image segmentation ...addition, artificial neural networks are often able to detect subtle patterns and ... See full document
6
Inflation Forecasting in Pakistan using Artificial Neural Networks
... of forecasting, there has been a great interest in studying the artificial neural network (ANN) forecasting in economics, financial, business and engineering applications including GDP growth, ... See full document
19
Forecasting Inflation Rates Using Artificial Neural Networks
... day forecasting, has placed a lot of interest in studying the artificial neural network (ANN) forecasting in economics, financial, business and engineering applications including GDP growth, ... See full document
7
COMPARATIVE ANALYSIS OF THE PERFORMANCE OF ARTIFICIAL NEURAL NETWORKS (ANNs) AND AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA) MODELS ON RAINFALL FORECASTING
... model evaluation of the trained ...various evaluation criteria to validate the performance of ...basic evaluation criteria were also used by Assis, Amran, Remali and Affendy (2010) for univariate ... See full document
6
The Usefulness of Artificial Neural Networks in Forecasting Exchange Rates
... Because exchange rates are influenced by many economic, political and psychological factors, it has been hard to identify a unique economic model that can provide reliable ...the exchange rate is most ... See full document
8
International Journal of Computer Science and Mobile Computing
... in Foreign Exchange Rates ...the foreign exchange market by taking a small subset of known information to reduce the effect of this uncertainty and ...on foreign exchange data ... See full document
6
Forecasting Exchange Rate Between Macedonian Denar and Euro Using Deep Learning
... the Artificial Intelligence (AI) and its application in various fields (Loshkovska & Koceski, 2015), starting from tourism (Koceski & Petrevska, 2012), through medicine (Trajkovik et ...of ... See full document
12
A New Approach to Predict Selective Critical Stock Indices Through Artificial Neural Networks and Chaos Theory
... a neural network which is capable of learning and concluded that neural network approach can significantly better thepredictability of stock price ...used Artificial Neural Networks to ... See full document
5
In Search of a Warning Strategy Against Exchange rate Attacks: Forecasting Tactics Using Artificial Neural Networks
... The prediction exercised here is performed in a discrete dynamics environment, based on the daily fluctuations of the interbank overnight interest rate, using artificial neural networks [r] ... See full document
18
Escalation of Forecasting Accuracy through Linear Combiners of Predictive Models
... Artificial neural networks (ANN) are mimicking the human brains way of learning and emulate human’s behavior for solving nonlinear complex ...financial forecasting such as index prediction, ... See full document
14
Forecasting Foreign Exchange Rates with the use of Artificial Neural Networks/Learning Machines and comparison with Traditional Concepts and Linear Models
... in forecasting the Arbitrage Pricing Theory (APT) (Refenes, 1994), including Yoon (1993) in forecasting bond ratings and stock ...of foreign exchange rate prediction (Franses and Grievensen, ... See full document
72
Forecasting Malaysian Exchange Rate: Do Artificial Neural Networks Work?
... Despite the random walk estimation, we examine the performance of two types of ANNs: Multi-layered feedforward network MLFN and General Regression Neural Network GRNN in predicting the e[r] ... See full document
13
Artificial Neural Networks in the Demand Forecasting of a Metal Mechanical Industry
... of artificial neural networks in demand forecasting present these techniques as reliable in the development of forecasts and point to the feasibility of their establishment in ... See full document
7
Forecasting solid waste generation in Juba Town, South Sudan using Artificial Neural Networks (ANNs) and Autoregressive Moving Averages (ARMA)
... presented in Table 2, from where we observed 1-1-1 (1 input layer, 1 hidden layer, and 1 output layer) gives an accurate prediction of the weekly solid waste output. Applying the rule-of-thumb method for estimating the ... See full document
13
Topological optimisation of artificial neural networks for financial asset forecasting
... data forecasting has long been an intriguing ...and forecasting is determined by the ANN’s topology, which is the interconnection between the processing elements (activation functions of hidden neurons) and ... See full document
179
Advanced approach to numerical forecasting using artificial neural networks
... ratic functions. Regarding to activation functions, both approximates input values. The diff erence is made with the extrapolation of input data, where better results for this precise data model bring MLP- NN. The ... See full document
8
FORECASTING OF DAILY NEED PRODUCT USING ARTIFICIAL NEURAL NETWORKS
... GFF networks, train certain output nodes to respond to certain input patterns and the changes in connection weights, due to learning, cause those same nodes to respond to more general classes of ... See full document
8
Smart Water: Short-Term Forecasting Application in Water Utilities
... Four of the abovementioned two-dimensional SOM (2D-SOM) were implemented to cluster the data. The four models change with the number (N) of neurons used in the 2D grid layer. For our purposes, N ranged between 2 and 5. ... See full document
70
Vol 7, No 9 (2017)
... and Artificial Neural Networks (ANN), are analyzed with different statistical ...of artificial intelligence technique and they try to improving the prediction models by ... See full document
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