Zobrazeno 1 - 10
of 784
pro vyhledávání: '"Mishra Pradeep"'
Autor:
Ray Soumik, Mishra Pradeep, Ayad Hicham, Kumari Prity, Sharma Rajnee, Kumari Binita, Al Khatib Abdullah Mohammad Ghazi, Tamang Anant, Biswas Tufleuddin
Publikováno v:
Journal of Horticultural Research, Vol 31, Iss 1, Pp 25-34 (2023)
Forecasting is valuable to countries because it enables them to make informed business decisions and develop data-driven strategies. Fruit production offers promising economic opportunities to reduce rural poverty and unemployment in developing count
Externí odkaz:
https://doaj.org/article/3aca0b550ecd4c93bbc82c4f1755041f
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., Priya S. R. Krishna, Naranammal N., Suman, Lal Priyanka, Mishra Pradeep, Abotaleb Mostafa, Alkattan Hussein
Publikováno v:
BIO Web of Conferences, Vol 97, p 00130 (2024)
Agriculture is the backbone of Indian Economy. Proper forecast of food crops and cash crops are necessary for the government in policy making decisions. The present paper aims to forecast Wheat and Sugarcane yield using Random Forest Regression. For
Externí odkaz:
https://doaj.org/article/921293146efc4cdb89394c34eec50785
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., Krishna Priya S. R., Razzaq Abbas Noor, Kausalya N., Yadav Shikha, Mishra Pradeep, Abotaleb Mostafa, Alkattan Hussein
Publikováno v:
BIO Web of Conferences, Vol 97, p 00142 (2024)
Sugarcane is the primary agricultural industry that sustains and promotes economic growth in India. In 2018, the majority of India's sugarcane production, specifically 79.9%, was allocated for the manufacturing of white sugar. A smaller portion, 11.2
Externí odkaz:
https://doaj.org/article/608392e9deb3497eac68f5f92eadda22
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
Publikováno v:
Green Processing and Synthesis, Vol 9, Iss 1, Pp 171-181 (2020)
Green synthesis is a simple, non-toxic, economical and eco-friendly approach for the synthesis of nanoparticles. In the present work, nanoparticles of titanium dioxide (TiO2 NPs) were synthesized using an aqueous solution of Syzygium cumini leaf extr
Externí odkaz:
https://doaj.org/article/06ddd52ab8cd401ab461be295ca2eae8
Autor:
Charles Oluwaseun Adetunji, Julius Kola Oloke, Mishra Pradeep, A. Peter Oluyori, Ravinder Singh Jolly, Oluwasesan Micheal Bello
Publikováno v:
Beni-Suef University Journal of Basic and Applied Sciences, Vol 7, Iss 4, Pp 505-510 (2018)
The use of synthetic herbicides poses a serious threat to environment, health and food safety. The development of safe and effective bioherbicides for selective control of weeds is thus the primary concern in crop production around the world. Efforts
Externí odkaz:
https://doaj.org/article/429b32b12bf54c249095d37078a1c92f