Improved short-term forecasting of space weather

Short-Term Weather Forecasting

Forecasting Space Weather

Forecasting space weather events presents the ultimate challenge to a space physics model. Not only should physical constraints be satisfied, but also practical issues such as timeliness, accuracy, and reliability must be adequately addressed. To address these needs, modern space weather forecasters and users rely on a great variety of space weather models, ranging from simple regressions and e...

Enhance the performance of weather parameters in Short-Term Weather forecasting using ANFIS

Weather prediction is an ever challenging area of investigation for scientists. The Adaptive Neuro-Fuzzy Inference System (ANFIS) has been widely used for modeling different kinds of nonlinear systems including rainfall forecasting. Adaptive Neuro-Fuzzy Inference Systems (ANFIS) combines the capabilities of Artificial Neural Networks (ANN) and Fuzzy Inference Systems (FIS) to solve different ki...

Improved generalized neuron model for short-term load forecasting

The conventional neural networks consisting of simple neuron models have various drawbacks like large training time for complex problems, huge data requirement to train a non linear complex problems, unknown ANN structure, the relatively larger number of hidden nodes required, problem of local minima etc. To make the Artificial Neural Network more efficient and to overcome the above-mentioned p...

Application of an Improved Neural Network Using Cuckoo Search Algorithm in Short-Term Electricity Price Forecasting under Competitive Power Markets

Accurate and effective electricity price forecasting is critical to market participants in order to make an appropriate risk management in competitive electricity markets. Market participants rely on price forecasts to decide on their bidding strategies, allocate assets and plan facility investments. However, due to its time variant behavior and non-linear and non-stationary nature, electricity...