標(biāo)題: Titlebook: Big Data Intelligence for Smart Applications; Youssef Baddi,Youssef Gahi,Loai Tawalbeh Book 2022 The Editor(s) (if applicable) and The Aut [打印本頁(yè)] 作者: Dopamine 時(shí)間: 2025-3-21 18:22
書目名稱Big Data Intelligence for Smart Applications影響因子(影響力)
書目名稱Big Data Intelligence for Smart Applications影響因子(影響力)學(xué)科排名
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書目名稱Big Data Intelligence for Smart Applications網(wǎng)絡(luò)公開度學(xué)科排名
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書目名稱Big Data Intelligence for Smart Applications被引頻次學(xué)科排名
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書目名稱Big Data Intelligence for Smart Applications年度引用學(xué)科排名
書目名稱Big Data Intelligence for Smart Applications讀者反饋
書目名稱Big Data Intelligence for Smart Applications讀者反饋學(xué)科排名
作者: 拋媚眼 時(shí)間: 2025-3-21 20:41
Conducting a Cardiopulmonary Exercise Test,tructure and function of the brain and which have proven effective in capturing the recurring characteristics of time series. In this context, we developed a model based on Recurrent Neural Networks for the prediction of equivalent noise levels produced by a road infrastructure. The model based on t作者: nonradioactive 時(shí)間: 2025-3-22 03:29
Cell Culture for Commercial Settings,e accuracy of almost 2% and a decrease of the prediction error. Based on the findings it can be concluded that the automated optimisation strategies are more efficient and provide a better set of parameters to use within an ANN model, so that an improved prediction accuracy can be achieved. Using th作者: EXULT 時(shí)間: 2025-3-22 07:00 作者: neoplasm 時(shí)間: 2025-3-22 11:27 作者: 迅速成長(zhǎng) 時(shí)間: 2025-3-22 15:38
Introduction to Cell and Tissue Cultureayes, Support Vector Classifier, Decision Tree, Random Forest, K-Nearest Neighbor, Logistic Regression had used to differentiate the depressed and non-depressed users. Finally, Support Vector Classifier outperforms among all of the investigated and evaluated techniques with 79.90% accuracy, 75.73% p作者: MUTED 時(shí)間: 2025-3-22 20:35
https://doi.org/10.1007/b102298adopting Big Data that can be resolved using Blockchain. Afterward, we overview the Blockchain technology by projecting its components, workflows, classification, and related characteristics. Finally, we present the importance of combining Big Data and Blockchain through reviewing the novel implemen作者: BYRE 時(shí)間: 2025-3-23 00:59 作者: 癡呆 時(shí)間: 2025-3-23 01:54
https://doi.org/10.1007/b102298he optimized and best prediction to find out the Fake news. To evaluate the proposed framework, three use cases with three different datasets has been developed during this study. The proposed framework will also help to understand what amount of data is responsible for detecting fake news, trying t作者: Presbyopia 時(shí)間: 2025-3-23 08:24
1860-949X through machine intelligence and big data models and techniques. This book is helpful for students and researchers as well as practitioners..978-3-030-87956-3978-3-030-87954-9Series ISSN 1860-949X Series E-ISSN 1860-9503 作者: Spongy-Bone 時(shí)間: 2025-3-23 12:44
Data Quality in the Era of Big Data: A Global Review,a quality. All these researches inspire us to review the most relevant findings and outcomes reported in this regard. Assuming that some review papers were already published for the same purpose, we believe that researchers always need an update. It is worth noting that all the published review pape作者: 保守 時(shí)間: 2025-3-23 14:52
Time Series Data Analysis Using Deep Learning Methods for Smart Cities Monitoring,tructure and function of the brain and which have proven effective in capturing the recurring characteristics of time series. In this context, we developed a model based on Recurrent Neural Networks for the prediction of equivalent noise levels produced by a road infrastructure. The model based on t作者: BAN 時(shí)間: 2025-3-23 19:50 作者: 危機(jī) 時(shí)間: 2025-3-24 01:39 作者: ascend 時(shí)間: 2025-3-24 05:46
NHS Big Data Intelligence on Blockchain Applications,on, these made it a good candidate for being applied to NHS medical records. Currently Blockchain technology, as one of the most important smart technologies, had been very widely used in smart applications that could influence the world. An analysis on such topic is provided in this chapter.作者: MUMP 時(shí)間: 2025-3-24 09:25
,Depression Detection from Social Media Using Twitter’s Tweet,ayes, Support Vector Classifier, Decision Tree, Random Forest, K-Nearest Neighbor, Logistic Regression had used to differentiate the depressed and non-depressed users. Finally, Support Vector Classifier outperforms among all of the investigated and evaluated techniques with 79.90% accuracy, 75.73% p作者: 外星人 時(shí)間: 2025-3-24 14:00
Securing Big Data-Based Smart Applications Using Blockchain Technology,adopting Big Data that can be resolved using Blockchain. Afterward, we overview the Blockchain technology by projecting its components, workflows, classification, and related characteristics. Finally, we present the importance of combining Big Data and Blockchain through reviewing the novel implemen作者: 演繹 時(shí)間: 2025-3-24 16:29
Big Data Based Smart Blockchain for Information Retrieval in Privacy-Preserving Healthcare System,are system. Our proposed Scheme initially utilizes an improved multi-transaction mode consortium block-chain constructed by different numbers of requests to the healthcare providers to achieve maximized appointment offers based on availability, transparency, and security. Our proposed Scheme is usef作者: 小故事 時(shí)間: 2025-3-24 21:42
FakeTouch: Machine Learning Based Framework for Detecting Fake News,he optimized and best prediction to find out the Fake news. To evaluate the proposed framework, three use cases with three different datasets has been developed during this study. The proposed framework will also help to understand what amount of data is responsible for detecting fake news, trying t作者: Urologist 時(shí)間: 2025-3-25 02:59 作者: temperate 時(shí)間: 2025-3-25 05:30
Introduction to Cardinal Arithmetices in human lives, the rise of adversarial attempts to manipulate those MLAs and influence their choices is not a surprise. The main goal of this paper is to present recent approaches, models and progresses in AMLs. Additionally, our goal is to focus on AML research trends and challenges.作者: Ondines-curse 時(shí)間: 2025-3-25 10:59
https://doi.org/10.1007/978-1-4614-6283-5ibuted clustering, classification, and prediction. Different distributed DM (DDM) techniques, MASs, the advantages of MAS-based DDM, and various MAS-based DDM approaches proposed by researchers are reviewed in this study.作者: ostrish 時(shí)間: 2025-3-25 13:18 作者: Vldl379 時(shí)間: 2025-3-25 17:48
Adversarial Machine Learning, Research Trends and Applications,es in human lives, the rise of adversarial attempts to manipulate those MLAs and influence their choices is not a surprise. The main goal of this paper is to present recent approaches, models and progresses in AMLs. Additionally, our goal is to focus on AML research trends and challenges.作者: Armory 時(shí)間: 2025-3-25 22:34
Multi-agent Systems for Distributed Data Mining Techniques: An Overview,ibuted clustering, classification, and prediction. Different distributed DM (DDM) techniques, MASs, the advantages of MAS-based DDM, and various MAS-based DDM approaches proposed by researchers are reviewed in this study.作者: 含沙射影 時(shí)間: 2025-3-26 02:50
A Conceptual Analysis of IoT in Healthcare,ossible using Wireless Body Area Network (WBAN). This chapter proposes a machine learning model to discover hidden facts and to predict the future behavior of patients based on current health conditions. Further, a conceptual analysis is presented using a heart disease dataset.作者: 本能 時(shí)間: 2025-3-26 08:17 作者: 朦朧 時(shí)間: 2025-3-26 11:29
Identification of Heavenly Bodies,at can prevent false identification of a mimicked walk or leg swing in sitting posture as a real walk activity, using conventional and convolutional deep learning algorithms. The system shows remarkable capability of identifying an actual walk from a mimicked walk activity using CNN 95% of the time.作者: crumble 時(shí)間: 2025-3-26 16:18 作者: 欺騙世家 時(shí)間: 2025-3-26 18:47
A Low-Cost IMU-Based Wearable System for Precise Identification of Walk Activity Using Deep Convoluat can prevent false identification of a mimicked walk or leg swing in sitting posture as a real walk activity, using conventional and convolutional deep learning algorithms. The system shows remarkable capability of identifying an actual walk from a mimicked walk activity using CNN 95% of the time.作者: CRP743 時(shí)間: 2025-3-26 23:38
Classification of Malicious and Benign Binaries Using Visualization Technique and Machine Learning s by combining DAISY and HOG features. Then a comparative study of machine learning algorithms leads us to a final efficient classifier that reaches an accuracy of 97,36% using Random Forest classification algorithm.作者: BROOK 時(shí)間: 2025-3-27 02:53 作者: CANE 時(shí)間: 2025-3-27 08:43 作者: 盤旋 時(shí)間: 2025-3-27 11:43 作者: Brochure 時(shí)間: 2025-3-27 13:55 作者: 惰性氣體 時(shí)間: 2025-3-27 21:30 作者: 流利圓滑 時(shí)間: 2025-3-28 00:19
Multi-agent Systems for Distributed Data Mining Techniques: An Overview,munication and coordination capabilities. This goal-oriented mechanism supports distributed data mining (DM) to implement various techniques for distributed clustering, classification, and prediction. Different distributed DM (DDM) techniques, MASs, the advantages of MAS-based DDM, and various MAS-b作者: Control-Group 時(shí)間: 2025-3-28 04:14
Time Series Data Analysis Using Deep Learning Methods for Smart Cities Monitoring,n the history of the variable of interest. They work by capturing patterns in historical data and extrapolating them into the future. The Times Series features recurring structures that can be captured through careful and precise analysis of its performance. Machine Learning-based methods are able t作者: 黃油沒有 時(shí)間: 2025-3-28 09:43 作者: Watemelon 時(shí)間: 2025-3-28 11:54
Facial Recognition Application with Hyperparameter Optimisation,ations utilise a certain set of hyperparameters to achieve the best recognition accuracy depending on the data set. There are several approaches to find the best set of these hyperparameters. They can be put into two categories: Manual optimisation and automated optimisation. By experimenting with b作者: 監(jiān)禁 時(shí)間: 2025-3-28 14:39
Internet-Assisted Data Intelligence for Pandemic Prediction: An Intelligent Framework,Data”. The growth of big data and the development of Internet of Things (IoT) technology have aided the viability of modern smart city initiatives. The governments and industries will use these technological advancements, as well as the widespread use of ubiquitous computing, to address healthcare r作者: infatuation 時(shí)間: 2025-3-28 19:48 作者: Maximizer 時(shí)間: 2025-3-29 01:28 作者: HIKE 時(shí)間: 2025-3-29 05:21 作者: 填滿 時(shí)間: 2025-3-29 10:42 作者: 冷漠 時(shí)間: 2025-3-29 12:30
Overview of Blockchain-Based Privacy Preserving Machine Learning for IoMT,e are many methods available to examine the IoMT data in a privacy-preserving manner but a study is needed to understand the best practical method for real life. So, this study will not propose a novel method but will explore the state-of-the-art method to address the most realistic method for priva作者: notion 時(shí)間: 2025-3-29 16:02
Big Data Based Smart Blockchain for Information Retrieval in Privacy-Preserving Healthcare System,mber of patient requests directly correlates with the slot availability. Existing smart healthcare systems facilitate the patient to reserve a particular time slot and attain real-time healthcare information. However, most of these systems need sensitive information about patients, i.e., desired des作者: 減至最低 時(shí)間: 2025-3-29 21:09
Classification of Malicious and Benign Binaries Using Visualization Technique and Machine Learning ike businesses and hospitals. Our main goal is to deliver an intelligent classifier as fast as efficient able to classifier binaries into malicious or benign classes. In this work, we consider a malware-benign classification using machine learning algorithms by converting binary executable files int作者: 旅行路線 時(shí)間: 2025-3-30 03:43
FakeTouch: Machine Learning Based Framework for Detecting Fake News,as become one of major threats that can harm someone’s reputation. It often circulates wrong or made up information about various products, events, people or entity. The deliberate making of such news is escalating drastically these days. Fake news deceives us in taking wrong decisions. Therefore, F作者: Narrative 時(shí)間: 2025-3-30 05:29
https://doi.org/10.1007/978-3-030-87954-9Computational Intelligence; Big Data; Artificial Intelligence; Smart City; IoT; Cyber-Physical Systems作者: GEM 時(shí)間: 2025-3-30 09:21 作者: Fsh238 時(shí)間: 2025-3-30 13:10 作者: CLAIM 時(shí)間: 2025-3-30 19:21 作者: Clumsy 時(shí)間: 2025-3-30 22:09
Introduction to Cardinal Arithmetic data is growing at a higher rate due to the variety of the data-generating adopted devices. In addition to the volume aspect, the generated data are usually unstructured, inaccurate, and incomplete, making its processing even more difficult. However, analyzing such data can provide significant bene作者: Aspiration 時(shí)間: 2025-3-31 03:13
Introduction to Cardinal Arithmetic Those MLAs make intelligence decisions on behalf of humans based on knowledge extracted from historical and current data. With such growth of MLA roles in human lives, the rise of adversarial attempts to manipulate those MLAs and influence their choices is not a surprise. The main goal of this pape
