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In this paper, two crop datasets are investigated. First one is numerical data which is downloaded crop dataset from https://github.com/Shrey-B/AV-Janatahack-Machine-Learning-in-Agriculture obtained from US field data collection. The... more
In this paper, two crop datasets are investigated. First one is numerical data which is downloaded crop dataset from https://github.com/Shrey-B/AV-Janatahack-Machine-Learning-in-Agriculture obtained from US field data collection. The dataset contains 88858 labeled samples, eight features and three classes. Second one is a collection of crop image data. This dataset is downloaded from https://www.kaggle.com/datasets/aman2000jaiswal/agriculture . Crop image dataset contains 1005 samples having five type of images namely maize, wheat, jute, rice and sugarcane. Each sample crop image consists of 224 × 224 pixels) of all category.
Research Interests:
Research Interests: Computer Science, Information Retrieval, Artificial Intelligence, Human Computer Interaction, Natural Language Processing, and 10 moreData Analysis, Data Management, Web search, Information Access, Finite Automata, Data acquisition, Bengali, Research and Development, Document representation, and Human Computer Interface
In this work, we proposed a method of artificial neural network learning using differential evolutionary(DE) algorithm. DE with global and local neighborhood based mutation(DEGL) algorithm is used to search the synaptic weight... more
In this work, we proposed a method of artificial neural network learning using differential evolutionary(DE) algorithm. DE with global and local neighborhood based mutation(DEGL) algorithm is used to search the synaptic weight coefficients of neural network and to minimize the learning error in the error surface.DEGL is a version of DE algorithm in which both global and local neighborhood-based mutation operator is combined to create donor vector.The proposed method is applied for classification of real-world data and experimental results show the efficiency and effectiveness of the proposed method and also a comparative study has been made with classical DE algorithm.