Expectation of Tourism Demand in Iraq by Using Artificial Neural Network

Abstract

This study survey and proves this effectiveness connected with artificial neural networks (ANNs) as an alternative approach in the tourism research. The learning utilizes the travel industry in the Japan being a method for estimating need to exhibit the solicitation. The outcome reveals the use of ANNs in tourism research might perhaps result in better quotations when it comes to prediction bias and accuracy. Even more applications of ANNs in the context of tourism demand examination is needed to establish and validate the effects. An ANN is based on a collection of connected units or nodes called artificial neurons, which loosely model the neurons in a biological brain. Each connection, like the synapses in a biological brain, can transmit a signal to other neurons. An artificial neuron that receives a signal then processes it and can signal neurons connected to it.

Application of Fuzzy Logic to Evaluate the Economic Impact of COVID-19: Case Study of a Project-Oriented Travel Agency

“…Therefore, in terms of formalizing inferential processes, the model provides only approximate answers in the analyses [34]. In order to overcome the disadvantage of the model, neural network and Bayesian-logic-based models are also used in the analyses, performance evaluation and controlling systems of the tourism sector [67][68][69][70][71].…”