Using Prescriptive Analytics for the Determination of Optimal Crop Yield
Terungwa Simon Yange,
Charity Ojochogwu Egbunu,
Malik Adeiza Rufai,
Oluoha Onyekwere,
Alao Abiodun Abdulrahman,
Idris Abdulkadri
Issue:
Volume 6, Issue 3, June 2020
Pages:
72-82
Received:
28 May 2020
Accepted:
8 June 2020
Published:
6 July 2020
Abstract: The application of data mining has been utilized in different fields ranging from agriculture, finance, education, security, medicine, research etc. Data mining derives useful information from careful examination of data. In Nigeria, Agriculture plays a critical role in the economy as it provides high level of employment for many people. It is typical of farmers in Nigeria to plant crops without paying considerate attention to the soil and crop requirements as most farmers inherit the lands used for farming from their fathers and just continue in the pattern of farming they had always known. This is not favorable in the level of productivity they can actually attain as the effect can be seen in same level of crop yield year after year if not even worse. Modern farming techniques make use of data mining from previous data considering soil types, and other factors like weather and climatic conditions. This study built a model that enables possible prediction of crop yield from the historic data collected and offers suggestions to farmers on the right soil nutrients requirements that would enhance crop yield. This will enable early prediction of crop yield and prior idea to improve on the soil to increase productivity. The research used XGBoost algorithm for the crop yield prediction and the Support Vector Machine algorithm for the recommendation of appropriate improvement of soil nutrient requirements. The accuracy obtained for the prediction with XGBoost was 95.28%, while that obtained for the recommendation of fertilizer using SVM was 97.86%.
Abstract: The application of data mining has been utilized in different fields ranging from agriculture, finance, education, security, medicine, research etc. Data mining derives useful information from careful examination of data. In Nigeria, Agriculture plays a critical role in the economy as it provides high level of employment for many people. It is typi...
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On the Flexibility of Topp Leone Exponentiated Inverse Exponential Distribution
Sule Ibrahim,
Sani Ibrahim Doguwa,
Audu Isah,
Haruna Muhammad Jibril
Issue:
Volume 6, Issue 3, June 2020
Pages:
83-89
Received:
1 May 2020
Accepted:
10 June 2020
Published:
17 July 2020
Abstract: In this paper, we introduced a new continuous probability distribution called the Topp Leone exponentiated inverse exponential distribution with three parameters. We studied the nature of proposed distribution with the help of its mathematical and statistical properties such as quantile function, ordinary moments, moment generating function, survival function and hazard function. The probability density function of order statistic for this distribution was also obtained. We performed classical estimation of parameters by using the technique of maximum likelihood estimate. The proposed model was applied to two real-life datasets. The first data set has to do with patients with cancer of tongue with aneuploidy DNA profile and the second data set has to do with patients who were diagnosed with hypertension and received at least one treatment related to hypertension. The results showed that the new distribution provided better fit than other distributions presented. As such, it can be categorically said that the Topp Leone exponentiated inverse exponential distribution is good distribution in modeling survival data.
Abstract: In this paper, we introduced a new continuous probability distribution called the Topp Leone exponentiated inverse exponential distribution with three parameters. We studied the nature of proposed distribution with the help of its mathematical and statistical properties such as quantile function, ordinary moments, moment generating function, surviv...
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Modeling Covariates of Infant and Child Mortality in Kenya
Stephen Muthii Wanjohi,
Daniel Mwangi Muriithi
Issue:
Volume 6, Issue 3, June 2020
Pages:
90-98
Received:
22 May 2019
Accepted:
9 July 2019
Published:
4 August 2020
Abstract: Mortality of children under the age of five has been target of public health policies. There has been a significant decline in under-five mortality in the twenty first century in almost all countries several studies have been conducted to identify covariates of Infant and Child Mortality in Kenya but none of these used recent data and none has included HIV/AIDs as a risk factor. This study aims at examining bio-demographic, socio-economic and environmental mortality in Kenya. Two methods of the logistic regression and survival analysis method are used. The results of the study show that HIV status of the mother and lengths of the preceding birth interval were significantly associated with both Infant and Child Mortality. Other significant covariates include birth order, age of the mother at birth of the child, sex of the child, education of the mother and father and wealth index.
Abstract: Mortality of children under the age of five has been target of public health policies. There has been a significant decline in under-five mortality in the twenty first century in almost all countries several studies have been conducted to identify covariates of Infant and Child Mortality in Kenya but none of these used recent data and none has incl...
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