Nowadays, airline ticket prices can vary dynamically and significantly for the same flight, even nearby seats within cabin. Customers are seeking to get lowest price while airlines trying keep their overall revenue as high possible maximize profit. Airlines use various kinds of computational techniques increase such demand prediction discrimination. From customer side, two models proposed by di...

To reduce the risk of people buying and increase rate return, applying a suitable model to predict stock prices is necessary. The research applies Long Short Term Memory (LSTM), which kind artificial neural network in machine learning also special RNN. Through studying this model, memory LSTM like human memory, composed short-term long-term accumulation. In paper, current data 2020 2021 train, ...

Stocks price analysis has been a critical area of research as the stock market is very fluctuating market. affected by demand and supply dynamics making it difficult to forecast at particular instant. The entire idea predicting stocks gain significant profits but how will perform task carry out. In an attempt do this, we construct dynamical system for stock’s simulate using Kalman filter. dynam...

The purpose of this paper is to estimate models for retail price of gasoline based on the prediction deriving from the recent infinitely repeated game theories, supergame theories. The prediction implies that both the future changes and the unexpected shock in the economic environment, where firms faces, do have an impact on the current retail price of gasoline. Using monthly time series data o...

this paper presents a fuzzy approach to the prediction of highly nonlinear timeseries.the optimized mamdani-type fuzzy system denoted sqp-flc is applied forthe input-output modeling of measured data. in order to tune fuzzy membershipfunctions, a sequential quadratic programming (sqp) method is employed. theproposed method is evaluated and validated on a highly complex time series, dailygold pri...

A large body of evidence shows that buying behaviour is strongly determined by consumers' price expectations and the extent to which real prices violate these expectations. Despite the importance of this phenomenon, little is known regarding its neural mechanisms. Here we show that two patterns of electrical brain activity known to index prediction errors-the Feedback-Related Negativity (FRN) a...

Grammatical Evolution (GE), which is one of the evolutionary computations, aims to find function, program or program segment satisfying the design objective. This paper describes the improvement of the Grammatical Evolution according to Stochastic Schemata Exploiter (GE-SSE) and its application to symbolic regression problem. Firstly, GE-SSE is compared with original GE in symbolic regression p...