Zobrazeno 1 - 10
of 32
pro vyhledávání: '"Albadran, Zainalabideen"'
Autor:
Yousif Mohammed Sahar, Aljanabi Mohammad, Mijwil Maad M., Ramadhan Ali J., Abotaleb Mostafa, Alkattan Hussein, Albadran Zainalabideen
Publikováno v:
BIO Web of Conferences, Vol 97, p 00059 (2024)
The goal of phishing assaults is to trick users into giving up personal information by making them believe they need to act quickly on critical information. The creation of efficient solutions, such as phishing attack detection systems backed by AI,
Externí odkaz:
https://doaj.org/article/702b355b0b1140509fb25a197c9ee60c
Autor:
Ramadhan Ali J., Biswas Tufleuddin, Ray Soumik, Anjanawe S. R., Rawat Deepa, Kumari Binita, Yadav Shikha, Mishra Pradeep, Abotaleb Mostafa, Alkattan Hussein, Albadran Zainalabideen
Publikováno v:
BIO Web of Conferences, Vol 97, p 00113 (2024)
The study aimed to compare ARIMA and Holt's models for predicting coconut metrics in Kerala. The coconut data series was collected from the period 1957 to 2019. Of this, 80% of the data (from 1957 to 2007) is treated as training data, and the rest (2
Externí odkaz:
https://doaj.org/article/8654b13d0353484d891b5bf1815f65e4
Autor:
Ramadhan Ali J., Yadav Shikha, Anand Subhash, Pratap Singh Aditya, Atta Kousik, Abotaleb Mostafa, Alkattan Hussein, Albadran Zainalabideen
Publikováno v:
BIO Web of Conferences, Vol 97, p 00124 (2024)
Delhi's Yamuna River serves as a notable illustration of an ecologically compromised system that has undergone a transition into a conduit for sewage due to pervasive pollution and escalating anthropogenic influences. Delhi, being the primary contrib
Externí odkaz:
https://doaj.org/article/962977cdae10415a87bb66f0a2a6e791
Autor:
Ramadhan Ali J., Krishna Priya S. R., Keerti Balambiga R., Othman Ali J., Yadav Shikha, Mishra Pradeep, Abotaleb Mostafa, Alkattan Hussein, Albadran Zainalabideen
Publikováno v:
BIO Web of Conferences, Vol 97, p 00064 (2024)
The present study aims to develop yield forecast models for the Sugarcane crop of the Coimbatore district in Tamilnadu using two different techniques namely Variables and Months in Discriminant function analysis. For this, the Sugarcane yield data fo
Externí odkaz:
https://doaj.org/article/d8ff36963e974d79bfd038e55df64d2b
Autor:
Ramadhan Ali J., Arun Kumar Bhukya, Bala Indu, Mijwil Maad M., Abotaleb Mostafa, Alkattan Hussein, Albadran Zainalabideen
Publikováno v:
BIO Web of Conferences, Vol 97, p 00154 (2024)
Through the use of smart sensors to monitor and regulate plant conditions, smart home gardening management systems can maximize resource utilisation and minimize human intervention. This study offers a new system that remotely controls the water supp
Externí odkaz:
https://doaj.org/article/34b69299210942d38d75d111c621dda4
Autor:
Ramadhan Ali J., Ray Soumik, Abotaleb Mostafa, Alkattan Hussein, Tiwari Garima, Rawat Deepa, Mishra Pradeep, Yadav Shikha, Tiwari Pushpika, Adebayo Adelaja Oluwaseun, Albadran Zainalabideen
Publikováno v:
BIO Web of Conferences, Vol 97, p 00126 (2024)
To model and forecast complex time series data, machine learning has become a major field. This machine learning study examined Moscow rainfall data's future performance. The dataset is split into 65% training and 35% test sets to build and validate
Externí odkaz:
https://doaj.org/article/a0f379b631e6493dab2ab97dac04bf77
Autor:
Ramadhan Ali J., Krishna Priya S. R., Naranammal N., Gautam Rajani, Mishra Pradeep, Ray Soumik, Abotaleb Mostafa, Alkattan Hussein, Albadran Zainalabideen
Publikováno v:
BIO Web of Conferences, Vol 97, p 00145 (2024)
Online shopping can be done from our convenient places like home, office, etc., and the product will be delivered to the respective places. There are many factors influencing online shopping. The purpose of this study is to develop a statistical mode
Externí odkaz:
https://doaj.org/article/e63be3c1bbf34eac907afeaf6efa3bae
Autor:
Ramadhan Ali J., Priya S. R. Krishna, Pavithra V., Mishra Pradeep, Dash Abhiram, Abotaleb Mostafa, Alkattan Hussein, Albadran Zainalabideen
Publikováno v:
BIO Web of Conferences, Vol 97, p 00157 (2024)
Weather has a profound influence on crop growth, development and yield. The present study deals with the use of weather parameters for sugarcane yield forecasting. Machine learning techniques like K- Nearest Neighbors (KNN) and Random Forest model ha
Externí odkaz:
https://doaj.org/article/c9350fd4411746c3994012707f3960e8
Autor:
Ramadhan Ali J., Krishna Priya S. R., Naranammal N., Pavishya S., Naveena K., Ray Soumik, Mishra P., Abotaleb Mostafa, Alkattan Hussein, Albadran Zainalabideen
Publikováno v:
BIO Web of Conferences, Vol 97, p 00078 (2024)
Sugarcane is the largest crop in the world in terms of production. We use sugarcane and its byproducts more and more frequently in our daily lives, which elevates it to the status of a unique crop. As a result, the assessment of sugarcane production
Externí odkaz:
https://doaj.org/article/e858a4c1b3204d719b7ff5522cb521f2
Publikováno v:
AIP Conference Proceedings; 2023, Vol. 2977 Issue 1, p1-9, 9p