[HTML][HTML] Application of a hybrid mechanistic/machine learning model for prediction of nitrous oxide (N2O) production in a nitrifying sequencing batch reactor

MJ Mehrani, F Bagherzadeh, M Zheng, P Kowal… - Process Safety and …, 2022 - Elsevier
Nitrous oxide (N 2 O) is a key parameter for evaluating the greenhouse gas emissions from
wastewater treatment plants. In this study, a new method for predicting liquid N 2 O …

An integrated risk prediction model for corrosion-induced pipeline incidents using artificial neural network and Bayesian analysis

P Kumari, SZ Halim, JSI Kwon, N Quddus - Process Safety and …, 2022 - Elsevier
In onshore hazardous liquid transmission pipelines, corrosion-induced incidents are
potentially significant hazard to people, property and environment. Therefore, several …

A blockchain-based multi-CA cross-domain authentication scheme in decentralized autonomous network

M Wang, L Rui, Y Yang, Z Gao… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The continuous development of network technology has driven the emergence of smart
devices, and the demand for smart devices interconnection has increased sharply, which …

Deep learning methods for damage detection of jacket-type offshore platforms

X Bao, T Fan, C Shi, G Yang - Process Safety and Environmental Protection, 2021 - Elsevier
Recently, big data and machine learning based damage detection methods to support risk
management of offshore facilities have received great attention, compared to traditional …

[HTML][HTML] Assessing the validity of navigation risk assessments: A study of offshore wind farms in the UK

A Rawson, M Brito - Ocean & Coastal Management, 2022 - Elsevier
The developments of offshore wind farms can place increased pressures on conflicting
marine users, particularly in already crowded waterways. Risk analysis of potential hazard …

A Bayesian model for predicting monthly fire frequency in Kenya

L Orero, EO Omondi, BO Omolo - PLoS one, 2024 - journals.plos.org
This study presents a comprehensive analysis of historical fire and climatic data to estimate
the monthly frequency of vegetation fires in Kenya. This work introduces a statistical model …

A data-driven danger zone estimation method based on bayesian inference for utility tunnel fires and experimental verification

X Liu, B Sun, ZD Xu, X Liu, D Xu - Journal of Performance of …, 2023 - ascelibrary.org
The ongoing challenge is to find an effective and precise fire detection method for safety
concerns of utility tunnels to predict the fire danger zone and take measures for firefighting …

[HTML][HTML] Восстановление параметров процесса образования событий в экономике, заданного алгоритмической моделью

ЮА Кораблев - Известия Кабардино-Балкарского научного …, 2022 - cyberleninka.ru
События в экономике изучаются с точки зрения процессов, которые происходят в
источниках этих событий. Процессы могут быть представлены произвольными …

Определение параметров процесса образования редких событий в экономике для их последующего прогнозирования

ЮА КОРАБЛЕВ - Экономика и математические методы, 2022 - elibrary.ru
В статье представлен метод определения неизвестных параметров процесса,
формирующего редкие события в экономике. Редкие события рассматриваются не со …

Prediction of the chances of death in covid-19 data using the poisson process

R Ashgi, S Supian - International Journal of Global Operations …, 2020 - iorajournal.org
Covid-19 has brought about major changes for all people in various countries, for example
creating vaccines, wearing masks and predicting the predictive state of death that will occur …