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A Model-Based Approach for Flight Delay Prediction
Methods: Logistic model with and without shrinkage was fit on an Airlines dataset of movements of 6585 domestic flights of 18 airlines in the United States and then, lasso, ridge and elastic net were used to improve the predictive ability.
Deep Recurrent Q-learning for Energy-constrained Coverage with a Mobile Robot
In this paper, we study the problem of coverage of an environment with an energy-constrained robot in the presence of multiple charging stations.
Fault Area Detection in Leaf Diseases using k-means Clustering
With increasing population the crisis of food is getting bigger day by day. In this time of crisis, the leaf disease of crops is the biggest problem in the food industry. In this paper, we have addressed that problem and proposed an efficient method to detect leaf disease. Leaf diseases can be detected from sample images of the leaf with the help of image processing and segmentation. Using k-means clustering and Otsu's method the faulty region in a leaf is detected which helps to determine proper course of action to be taken. Further the ratio of normal and faulty region if calculated would be able to predict if the leaf can be cured at all.
