Furthermore, introduced a new forecast model based on BP neural network, a real diagnosis is done by the investigated data, the results show that the bullwhip effect and their variable are different due to diff
This paper aims to compare the performance of different Artificial Neural Networks techniques for tourist demand forecasting. We test the forecasting accuracy of three different types of architectures: a multi-layer perceptron, a radial basis function and an Elman network. We also evaluate the effect...
2016). To overcome the issue, numerous studies have exploited machine and deep learning techniques in OD demand prediction, such as convolutional neural networks (Ke et al. 2017), stacked gradient boosting decision trees (W. Wu, Xia, and Jin 2021), and long short-term memory (Baghbani, Bo...
The proposed work includes both point forecasting and interval forecasting techniques in wind speed prediction. The point prediction errors are characterised using suitable statistical distribution and quantified by means of confidence intervals and coverage rate. The work, in the first stage, forecasts th...
effective cognitive tools and strategies offer extraordinary potential benefits. Structured decision-making frameworks can help us avoid costly errors. Mental models can illuminate connections we’d otherwise miss. Debiasing techniques can protect us from systematic reasoning flaws. Forecasting methodologies can...
Quality control is a critical component of flow production scheduling in the automotive industry. Manufacturers use a variety of tools and techniques to ensure that each vehicle meets strict quality standards before it leaves the assembly line. ...
What is the purpose of forecasting? When is the best time to forecast? What is a "foreign exchange rate"? What are Quantitative methods? What techniques can a risk manager use to predict future losses? What are the methods of conducting trade? What is the difference between a spot market...
Particle size significantly influences handling, storage, granulation techniques, and agronomic responses. To accurately measure the particle sizes, 30 random fertilizer samples were selected, each corresponding to a different type of composition according to Tables 4 and 5, as shown in Fig. 2a and ...
Here, we apply efficient, gradient-based optimization techniques with full knowledge of the analytical gradients. The workflow's main idea is to translate the different process models into generic CasADi optimization syntax. Compared to data-driven MPC approaches in scientific literature, which often ...
Different optimization techniques can be investigated to get the optimum parameters for maximum power that can be extracted from the wave turbine. In this study, the WOA is chosen to be used for finding the optimal parameters of Savonius wave turbine due to its high speed for reaching the ...