Titlebook: Data Science and Big Data Analytics; Proceedings of IDBA Durgesh Mishra,Xin She Yang,Dharm Singh Jat Conference proceedings 2024 The Edito

環(huán)形

Ebct207

https://doi.org/10.1007/978-1-4419-7148-7doop and Map Reduce are helping to store and handle this large volume of data. However, the storage and security are major concerns. Data redundancy is a common problem in cloud and big data. De-duplication methods are commonly used to improve the efficiency of storage in cloud and can save network

否認(rèn)

果核

最低點(diǎn)

vector

Monotonic Strength and Fractureictions, environmental monitoring and water shortage. In this work, support vector regression and decision tree techniques have been applied on the given datasets. The data used in this experiment is classified into two different parts: soil moisture data and meteorological data. The data is collect

眨眼

Monotonic Strength and Fracturepparel. The empirical study looks at how customer satisfaction, security, reliability, convenience, trust, functionality, and behavioral intention toward online commerce interact. Security, reliability, convenience, trust, and functionality were used to gauge the quality of the service. Behavioral i

符合規(guī)定

性別

Materials Research and Engineeringopment life cycle. Deep learning (DL), machine learning (ML), and all forms of data mining are used in the process of predicting software faults. First, we provide a brief introduction to the fundamentals of ML-based software defect prediction. The objective of software fault prediction is to identi

外面

Strength, Fracture, Fatigue, and Designd materials research. The integration of artificial intelligence (AI) into nanotechnology has created a new area of research and innovation known as AI-nanotechnology. This integration has resulted in significant advancements in the field of nanotechnology, including the development of new materials