MapReduce-based big data classification model using feature subset selection and hyperparameter tuned deep belief network

Rajendran, Surendran; Khalaf, Osamah Ibrahim; Alotaibi, Youseef; Alghamdi, Saleh

doi:10.1038/s41598-021-03019-y

Cited by 124 publications

(106 citation statements)

References 32 publications

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“…Because extracting some data can only reflect local results, there are many drawbacks. Big data analysis can accurately understand the market development situation, clarify the market positioning, and achieve the purpose of precise marketing [10,11]. Therefore, big data can improve the decision-making power of enterprises and improve the efficiency of enterprise management.…”

Section: Relevant Research Theories Of Rural Tourismmentioning

confidence: 99%

The Development Path and Data Mining Mode of Rural Tourism under the Background of Big Data

Chen

et al. 2022

Wireless Communications and Mobile Computing

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With the advent of the era of mass tourism, rural tourism has received increasing attention from tourism-related personnel, such as the wide application of Internet, cloud computing, and big data technology, making it possible to build a development path for rural tourism based on the background of big data. The purpose of this paper is to study the development path and data mining mode analysis of rural tourism under the background of data and propose a clustering integration algorithm. The article gives an overview of the fit relationship between rural tourism and big data. This paper takes the farm tourism data in area A as the research object and through the data analysis of the rural tourism development path using the clustering integration algorithm; it explores the effectiveness of the clustering integration algorithm in the construction of the rural tourism development path. The experimental results show that compared with the traditional rural tourism development model in 2020, the tourism revenue in 2021 will increase by more than 300,000 yuan.

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Section: Relevant Research Theories Of Rural Tourismmentioning

confidence: 99%

The Development Path and Data Mining Mode of Rural Tourism under the Background of Big Data

Chen

et al. 2022

Wireless Communications and Mobile Computing

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“…In Wireless Sensor Networks (WSN), nodes communicate with one another by using wireless techniques and through certain routing algorithms. In [29,30], the authors proposed an Energy Efficient Routing and Reliable Data Transmission Protocol for wireless sensor nodes. In WSN, the size of the nodes are very small, hence the energy efficient mechanisms play a vital role.…”

Section: Related Workmentioning

confidence: 99%

Authentication and Resource Allocation Strategies during Handoff for 5G IoVs Using Deep Learning

Hemavathi¹,

Akhila²,

Alotaibi

et al. 2022

Energies

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One of the most sought-after applications of cellular technology is transforming a vehicle into a device that can connect with the outside world, similar to smartphones. This connectivity is changing the automotive world. With the speedy growth and densification of vehicles in Internet of Vehicles (IoV) technology, the need for consistency in communication amongst vehicles becomes more significant. This technology needs to be scalable, secure, and flexible when connecting products and services. 5G technology, with its incredible speed, is expected to power the future of vehicular networks. Owing to high mobility and constant change in the topology, cooperative intelligent transport systems ensure real time connectivity between vehicles. For ensuring a seamless connectivity amongst the entities in vehicular networks, a significant alternative to design is support of handoff. This paper proposes a scheme for the best Road Side Unit (RSU) selection during handoff. Authentication and security of the vehicles are ensured using the Deep Sparse Stacked Autoencoder Network (DS2AN) algorithm, developed using a deep learning model. Once authenticated, resource allocation by RSU to the vehicle is accomplished through Deep-Q learning (DQL) techniques. Compared with the existing handoff schemes, Reinforcement Learning based on the MDP (RL-MDP) has been found to have a 13% lesser decision delay for selecting the best RSU. A higher level of security and minimum time requirement for authentication is achieved using DS2AN. The proposed system simulation results demonstrate that it ensures reliable packet delivery, significantly improving system throughput, upholding tolerable delay levels during a change of RSUs.

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“…Finally, the clustering features of the corresponding subclusters of the final CF leaf element are output to the next stage of the algorithm. As shown in from formulas ( 1 ) to ( 9 ) [ 16 , 17 ].

where

represents the linear summation of the attribute values of the data points in cluster C _ j .…”

Section: Internet Of Things Big Data Processing Technologymentioning

confidence: 99%

Online Shopping Brand Sales Based on IoT Big Data Processing

Zhang

2022

Computational Intelligence and Neuroscience

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As a pair of closely related technical fields, “Internet of Things” and “big data” are gradually applied to the analysis of online shopping, which is very beneficial to promote the healthy and orderly development of the online shopping industry. This article uses the big data processing technology of the Internet of Things to analyze the influencing factors of online shopping brand sales based on the data collected by online questionnaires. It draws certain rules from it, and provides relevant marketing strategies for online shopping brand sales to assist its market positioning. According to the survey, the five aspects of online evaluation, brand awareness, online shopping community, online public opinion influence of related brands, and other brand information acquisition channels all have an impact on online brand sales. Especially women aged 25–35 will pay attention to online information, and 195 people will not choose to buy from brands with negative news. And during the purchase process, 186 people will check the online reviews of related brand products. Among them, there are 183 men aged 25–35 who will pay attention to online reviews.

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MapReduce-based big data classification model using feature subset selection and hyperparameter tuned deep belief network

Cited by 124 publications

References 32 publications

The Development Path and Data Mining Mode of Rural Tourism under the Background of Big Data

The Development Path and Data Mining Mode of Rural Tourism under the Background of Big Data

Authentication and Resource Allocation Strategies during Handoff for 5G IoVs Using Deep Learning

Online Shopping Brand Sales Based on IoT Big Data Processing

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