As Bangladesh is an agricultural country, cows have a great influence on our economy. However, there no cow-related work or dataset accessible online in the fields of machine learning and artificial intelligence. This study aims to predict cow price ranges using any picture. Cow images were collected from different e-commerce sites which are selling mainly attempted range based cows. Cows divid...

This paper discusses, trying to accurately assess the price of Bitcoin by looking at different parameters affects value Bitcoin. In our work, we focus on understanding and seeing evolution daily market, a1 gaining intuition in most relevant aspects surrounding price. meantime, market capitalization publicly traded cryptocurrencies exceeds $ 230 billion. The important cryptocurrency, Bitcoin, is...

This paper proposes a novel non-parametric approach for the analysis and prediction of electricity price curves by applying the manifold learning methodology. Cluster analysis based on the embedded low-dimensional manifold of the original price data is employed to identify characteristics of the price curve shape. The proposed price curve model performs well in forecasting both short-term price...

Considering the fact that natural gas is a widely used energy source,  the prediction of its consumption can be useful (Derek LAM, 2013). As Iran has one of the largest gas reserves in the world, its consumption in the country can affect the worldwide price of gas, Therefore, the current research is useful both from economic and environmental point of view. ...

We introduce a new method of varying risk that bidders face in first-price and second-price private value auctions. We find that decreasing bidders’ risk in first-price auction reduces the degree of overbidding relative to the risk-neutral Bayesian-Nash equilibrium prediction. This finding is consistent with the risk-aversion explanation of overbidding. Furthermore, we apply the method to secon...