[PDF][PDF] Experimental prediction of the discharge coefficients for rectangular weir with bottom orifices

HH Alwan, LA Saleh, FM Al-Mohammed… - Journal of …, 2020 - researchgate.net
Weir is a hydraulic structure used to regulate and measure flow in irrigation projects. In order
to increase the discharge capacity of the weirs and minimize upstream sedimentation, weirs …

Waiting-time estimation in bank customer queues using RPROP neural networks

RPS Hermanto, A Nugroho - Procedia Computer Science, 2018 - Elsevier
In daily banking customer queues, unknown waiting-time could lower customer experience.
Little's Law formula in Queue Theory provides a generic formula for waiting-time, but it …

Applications of statistical techniques and artificial neural networks: A review

DS Jat, P Dhaka, A Limbo - Journal of Statistics and Management …, 2018 - Taylor & Francis
Big data is everywhere, and storage is affordable. The existing hardware and software are
unable to analysis the vast amount of various types of data. Big data has become too …

Development and comparative analysis of ANN and SVR-based models with conventional regression models for predicting spray drift

G Moges, K McDonnell, MA Delele, AN Ali… - … Science and Pollution …, 2023 - Springer
As monitoring of spray drift during application can be expensive, time-consuming, and labor-
intensive, drift predicting models may provide a practical complement. Several mechanistic …

Application of a multilayer perceptron artificial neural network for identification of peach cultivars based on physical characteristics

AM Al-Saif, M Abdel-Sattar, AM Aboukarima, DH Eshra - PeerJ, 2021 - peerj.com
In the fresh fruit industry, identification of fruit cultivars and fruit quality is of vital importance.
In the current study, nine peach cultivars (Dixon, Early Grande, Flordaprince, Flordastar …

A comparative study of linear and nonlinear regression models for outlier detection

PI Dalatu, A Fitrianto, A Mustapha - … on Soft Computing and Data Mining …, 2017 - Springer
Abstract Artificial Neural Networks provide models for a large class of natural and artificial
phenomena that are difficult to handle using classical parametric techniques. They offer a …

Antecedent factors of violation of information security rules

A Cappellozza, GHSM Moraes, G Perez… - RAUSP Management …, 2022 - SciELO Brasil
Purpose This paper aims to investigate the influence of moral disengagement, perceived
penalty, negative experiences and turnover intention on the intention to violate the …

Towards property valuation accuracy: a comparison of hedonic pricing model and artifiical neural network

RB Abidoye - 2017 - theses.lib.polyu.edu.hk
The need for accurate property valuation in any country cannot be underestimated due to
the significant relationship between the real estate industry and the national economy …

A data driven methodology for social science research with left-behind children as a case study

C Wu, G Wang, S Hu, Y Liu, H Mi, Y Zhou, Y Guo… - Plos one, 2020 - journals.plos.org
For decades, traditional correlation analysis and regression models have been used in
social science research. However, the development of machine learning algorithms makes it …

[PDF][PDF] Electricity demand forecasting: A review

E Efekemo, EG Saturday, JC Ofodu - Educ. Res. IJMCER, 2022 - ijmcer.com
Electricity forecasting is a very important tool in the energy industry. Electricity demand
forecasting is an essential part of the electricity industry. It is widely used for planning …