Results 151 to 160 of about 57,230 (310)

A Bayesian Analysis of Accidental Dwelling Fire Incidence, Injury, and Fatality in the Greater Manchester Area

Fire and Materials, EarlyView.
ABSTRACT The relationship between accidental dwelling fire incidence and fire injury and fatality was examined using a Bayesian model to estimate the probability of a fire injury or fatality resulting from an accidental dwelling fire incidence under different circumstances of fire incidence (type of accidental dwelling fire, dwelling occupancy type ...
M. Taylor, E. Dean, R. Lyon, V. Kwasnica, D. Reilly, H. Francis   +5 more
wiley   +1 more source

Optimised Internet of Thing framework based hybrid meta‐heuristic algorithms for E‐healthcare monitoring

IET Networks, EarlyView., 2022
Abstract Everything can be connected in the Internet of Things (IoTs) technology that enables efficient communication between connected objects. IoTs industry‐based meta‐heuristic and mining algorithms, which are considered an important field of Artificial Intelligence will be used to construct a healthcare application in this study for lowering costs,
Muhaned Al‐Hashimi, Shymaa Mohammed Jameel, Firas Husham Almukhtar, Musaddak Maher Abdul Zahra, Refed Adnan Jaleel   +4 more
wiley   +1 more source

Chemical named entity recognition in the texts of scientific publications using the naïve Bayes classifier approach. [PDF]

J Cheminform, 2022
Tarasova OA, Rudik AV, Biziukova NY, Filimonov DA, Poroikov VV.   +4 more
europepmc   +2 more sources

Naïve Bayes evidence accumulation K-modes clustering: A new method for classifying binary data and its application on real data of injecting drug users

Journal of Biostatistics and Epidemiology, 2018
Background & Aim: Clustering is the method of classifying discrete data such as Kmodes, and Naïve Bayes classifier is the classification to predict the unknown real classes.
Zahra Zamaninasab, Hamid Sharifi, Abbas Bahrampour   +2 more
doaj  

Predicting EU Emissions Allowance Prices Using Macroeconomic Indicators and Hybrid AI Models

Journal of Forecasting, EarlyView.
ABSTRACT Predicting carbon allowance prices has grown more crucial in relation to carbon market regulation, financial strategy, and environmental policy development. This study examines a hybrid forecasting system that combines deep learning with ensemble machine learning models to forecast the price fluctuations of EU Emissions Allowance (EUAs) within
Saptarshi Ganguly, Pooja Sengupta, Divya Aggarwal   +2 more
wiley   +1 more source

Intent Arabic text categorisation based on different machine learning and term frequency

IET Networks, EarlyView., 2022
Abstract The complexity of Internet network configurations has made managing networks a complicated undertaking. Intent‐Based Networking (IBN) is a potential solution to this issue. In contrast to conventional networks, where a concrete description of the settings typically conveys a network administrator's goal kept on each device, an administrator's ...
Mohammad Fadhil Mahdi, Mahmoud Shuker Mahmoud   +1 more
wiley   +1 more source

CUSTOMER BEHAVIOR PREDICTION USING NAÏVE BAYES [PDF]

In the business world, knowing the behavior of each user or customer is an important and crucial thing. The main reason that makes customer behavior and habits important is because by paying attention to customer behavior, businesses can provide the ...
VIVIAN.C, ELISABET STEVANI
core  

Klasifikasi Kebakaran Hutan dan Lahan Menggunakan Algoritma Naïve Bayes Classifier

Abstrak: Salah satu bencana alam yang sering terjadi di Indonesia adalah kebakaran. Pada tahun 2019, terdapat 1.124 titik panas di Kalimantan Barat. Kebakaran hutan menyebabkan banyak kerugian, termasuk deforestasi hutan dan hasilnya, pencemaran kabut ...
Deni, Deni Deni, Utami, Putri Yuli, Octariadi, Barry Ceasar   +2 more
core   +1 more source

Creation of a Landslide Susceptibility Map Using Short‐Term Data From the July 2018 Heavy Rainfall in Southern Hiroshima Prefecture

Geological Journal, EarlyView.
This work advances landslide susceptibility mapping by incorporating short‐term trigger data with landscape susceptibility mapping. We also examine the importance of downsampling, watershed delineation and geospatial correlations in evaluating outcomes.
Kanta Kotsugi, Ting Liu, Toshiro Hata, Rebecca Muenich   +3 more
wiley   +1 more source

Trigonometric words ranking model for spam message classification

IET Networks, EarlyView., 2022
Abstract The significant increase in the volume of fake (spam) messages has led to an urgent need to develop and implement a robust anti‐spam method. Several of the current anti‐spam systems depend mainly on the word order of the message in determining the spam message, which results in the system's inability to predict the correct type of message when
Suha Mohammed Hadi, Ali Hakem Alsaeedi, Dhiah Al‐Shammary, Zaid Abdi Alkareem Alyasseri, Mazin Abed Mohammed, Karrar Hameed Abdulkareem, Riyadh Rahef Nuiaa, Mustafa Musa Jaber   +7 more
wiley   +1 more source