Financial time series prediction using artificial neural network based on Levenberg-Marquardt algorithm
نویسندگان
چکیده
منابع مشابه
Calibration of an Inertial Accelerometer using Trained Neural Network by Levenberg-Marquardt Algorithm for Vehicle Navigation
The designing of advanced driver assistance systems and autonomous vehicles needs measurement of dynamical variations of vehicle, such as acceleration, velocity and yaw rate. Designed adaptive controllers to control lateral and longitudinal vehicle dynamics are based on the measured variables. Inertial MEMS-based sensors have some benefits including low price and low consumption that make them ...
متن کاملAvailability Prediction of the Repairable Equipment using Artificial Neural Network and Time Series Models
In this paper, one of the most important criterion in public services quality named availability is evaluated by using artificial neural network (ANN). In addition, the availability values are predicted for future periods by using exponential weighted moving average (EWMA) scheme and some time series models (TSM) including autoregressive (AR), moving average (MA) and autoregressive moving avera...
متن کاملVehicle's velocity time series prediction using neural network
This paper presents the prediction of vehicle's velocity time series using neural networks. For this purpose, driving data is firstly collected in real world traffic conditions in the city of Tehran using advance vehicle location devices installed on private cars. A multi-layer perceptron network is then designed for driving time series forecasting. In addition, the results of this study are co...
متن کاملTime Series Prediction Based on Multiple Artificial Neural Network
Time series prediction is a challenging research area with broad application prospects. Accurate time series prediction can provide important information for the relevant decision-makers. Many works extended different architecture of artificial neural networks to work with time series prediction, but they mostly only consider the time series itself, does not weigh the impact of relevant time se...
متن کاملNanofluid Thermal Conductivity Prediction Model Based on Artificial Neural Network
Heat transfer fluids have inherently low thermal conductivity that greatly limits the heat exchange efficiency. While the effectiveness of extending surfaces and redesigning heat exchange equipments to increase the heat transfer rate has reached a limit, many research activities have been carried out attempting to improve the thermal transport properties of the fluids by adding more thermally c...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Procedia Computer Science
سال: 2017
ISSN: 1877-0509
DOI: 10.1016/j.procs.2017.11.285