Time Series ANN Approach for Weather Forecasting

Kumar, Neeraj; Jha, Govind Kumar

doi:10.5121/ijctcm.2013.3102

Cited by 20 publications

(18 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Artificial neural network (ANN) methods have attracted extensive attention in the time series prediction field [9]. ANNs are universal nonlinear regression techniques, and are able to be applied into time series prediction conveniently [10].…”

Section: Introductionmentioning

confidence: 99%

Time Series Prediction Based on Adaptive Weight Online Sequential Extreme Learning Machine

Huang

Lü

2017

Applied Sciences

View full text Add to dashboard Cite

A novel adaptive weight online sequential extreme learning machine (AWOS-ELM) is proposed for predicting time series problems based on an online sequential extreme learning machine (OS-ELM) in this paper. In real-world online applications, the sequentially coming data chunk usually possesses varying confidence coefficients, and the data chunk with a low confidence coefficient tends to mislead the subsequent training process. The proposed AWOS-ELM can improve the training process by accessing the confidence coefficient adaptively and determining the training weight accordingly. Experiments on six time series prediction data sets have verified that the AWOS-ELM algorithm performs better in generalization performance, stability, and prediction ability than the OS-ELM algorithm. In addition, a real-world mechanical system identification problem is considered to test the feasibility and efficacy of the AWOS-ELM algorithm.

show abstract

Section: Introductionmentioning

confidence: 99%

Time Series Prediction Based on Adaptive Weight Online Sequential Extreme Learning Machine

Huang

Lü

2017

Applied Sciences

View full text Add to dashboard Cite

show abstract

“…An Artificial Neural Network (ANN) is an artificial representation of human brain that tries to simulate its learning process [3]. The word neural network is referred to a network of biological neuron in the nervous system that process and transmit the information.…”

Section: Neural Network Modelmentioning

confidence: 99%

Short-term Wind Speed Prediction Based on ANN in the Region of Rajasthan, India

2018

IJMTER

View full text Add to dashboard Cite

Abstract-Short-term wind speed forecasting is useful for power system to regulate power dispatching plan, decrease reserve power needed and increase the reliability of system. The method of the short-term wind speed prediction is proposed in this paper. The data of wind speed in a region of Rajasthan, India is predicted by the Artificial Neural Network. In this paper, the wind speed measured at 15minutes of 24 hours on 5 June, 2017 are the initial dataset for predicting.

show abstract

“…(5) ( )∑ (6) The weights are calculated with regard to (6), where the necessary change in weights is computed based on the learning rate α: (7) where e = the order of the weight updates in the learning process. The second phase of the BPTT algorithm continues to process (the folding process) when the back propagation algorithm is used to obtain the FFN.…”

Section: F Back Propagation Through Time Neural Networkmentioning

confidence: 99%

“…Artificial neural network (ANN) can be simulated via MATLAB to predict maximum and minimum temperatures (two important weather parameters). Based on findings of this research, multilayer neural network predicts weather as a powerful method that correctly provides mapping between input and output by using historical data [6].…”

Section: Introductionmentioning

confidence: 99%