Application of Machine Learning to the Process of Crop Selection Based on Land Dataset
Keywords:
Artificial Neural Network, Convolutional Neural Network, Research on Cancer, Computer Aided Detection, Data Flow Diagram
Abstract
We are well recognised that the vast majority of Indians work in agriculture. Most farmers always grow the same thing, always use the same amount of fertilizer, and always plant what the people want. Recently, there have been many breakthroughs in the use of machine learning in many fields of study and business. Thus, we intend to establish a framework for the application of machine learning in agriculture for the benefit of farmers. India's economy relies heavily on the nation's agricultural output. Agriculture, then, has the potential to serve as the backbone of the Philippine economy. Choosing the right crop every time is crucial when making agricultural plans. Researchers have utilised machine learning to explore agricultural issues such as crop yield, weather prediction, soil categorization, and crop labelling. Our Indian economy really needs the agricultural sector to undergo significant reforms. Simple applications of machine learning systems in agriculture have the potential to significantly enhance this industry. In addition to the considerable role played by improvements in farming machinery and technology, functional information about many subjects also plays an important role. The main idea of this study is to use the crop selection approach in order to address numerous issues in farming. This increases the wealth of India by increasing crop yields to their maximum potential. In our study, we use the method Random Forest (RF) to estimate a crop and then evaluate its performance relative to that of competing techniques
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33. S Ningthoujam, T Chingkheinganba, S K Chakraborty, A Elngar, Prasun Chakrabarti, Tulika Chakrabarti, Praveen, S. Phani, Amit Gupta, Margala, Martin, “Performance Analysis for Molecular Communication Under Feedback Channel Using Multipath and Single Path Technique”, Pre-print, 2022.
34. Pankaj Chittora, Tulika Chakrabarti, Papiya Debnath, Amit Gupta, Prasun Chakrabarti, S Phani Praveen, Martin Margala, Ahmed A Elngar, “Experimental analysis of earthquake prediction using machine learning classifiers, curve fitting, and neural modeling”, Pre-print, 2022.
35. Umesh Agarwal, Abrar Ahmed Chhipa, Tulika Chakrabarti, Amit Gupta, S Phani Praveen, Prasun Chakrabarti, Neha Sharma, Ahmed A Elngar, “Reliability Evaluation of Radial Distribution Network for Educational purpose using Greedy Search Approach-Distribution Network Data and Results”, Pre-print, 2022.
36. Nagendra Singh, Manish Tiwari, Tulika Chakrabarti, Prasun Chakrabarti, Om Prakash Jena, Ahmed A Elngar, Vinayakumar Ravi, Martin Margala, “Minimization of Environmental Emission and cost of generation by using economic load dispatch”, Pre-print, 2022.
37. Akhilesh Deep Arya, Sourabh Singh Verma, Prasun Chakrabarti, Tulika Chakrabarti, Ahmed A Elngar, Mohammad Nami, Ali-Mohammad Kamali, “A Systematic Review on Machine Learning and Deep Learning Techniques in the Effective Diagnosis of Alzheimer’s Disease”, Pre-print, 2022
38. Suchismita Gupta, Bikramjit Sarkar, Subhrajyoti Saha, Indranath Sarkar, Prasun Chakrabarti, Sudipta Sahana, Tulika Chakrabarti, Ahmed A Elngar, “A Novel Approach Toward the Prevention of the Side Channel Attacks for Enhancing the Network Security”, Pre-print, 2022.
39. Naveen S Pagad, N Pradeep, Tulika Chakrabarti, Prasun Chakrabarti, Ahmed A Elngar, Martin Margala, Mohammad Nami, Neha Sharma, Samuel Frimpong, “Clinical XLNet-based End-to-End Knowledge Discovery on Clinical Text Data using Natural Language Processing”, Pre-print, 2022
40. K Suvarna Vani, Bui Thanh Hung, Prasun Chakrabarti, Tulika Chakrabarti, Ahmed A Elngar, “Detection and Classification of Invasive Ductal Carcinoma using Artificial Intelligence”, Pre-print, 2022.
41. KS Balamurugan, Prasun Chakrabarti, Tulika Chakrabarti, Amit Gupta, Ahmed A Elngar, Mohammad Nami, Vinayakumar Ravi, Grienggrai Rajchakit, M Ali Akbar, “Improving the Performance of Diagnosing Chronic obstructive Lung Disease Using Outlier Detection with Decision Tree Algorithm”, Pre-print, 2022.
42. Ruhul Amin Hazarika, Arnab Kumar Maji, Debdatta Kandar, Prasun Chakrabarti, Tulika Chakrabarti, KS Jagannatha Rao, Jose Carvalho, Babak Kateb, Mohammad Nami, “An evaluation on changes in Hippocampus size for Cognitively Normal (CN), Mild Cognitive Impairment (MCI), and Alzheimer’s disease (AD) patients using Fuzzy Membership Function”, OSF Preprints, 2021.
43. Jitendra Shreemali, Prasun Chakrabarti, Tulika Chakrabarti, Sandeep Poddar, Daniel Sipple, Babak Kateb, Mohammad Nami, “A Machine Learning Perspective on Causes of Suicides and identification of Vulnerable Categories using Multiple Algorithms”, medRxiv, 2021.
44. Papiya Debnath, Pankaj Chittora, Tulika Chakrabarti, Prasun Chakrabarti, Zbigniew Leonowicz, Michal Jasinski , Radomir Gono, Elżbieta Jasińska, “Analysis of earthquake prediction in India using supervised machine learning classifiers”, Sustainibility ,13(2):971 , 2021.
45. 21. Pankaj Chittora, Sandeep Chaurasia, Prasun Chakrabarti, Gaurav Kumawat, Tulika Chakrabarti, Zbigniew Leonowiz, Michael Jaisinski, Lukasz Jaisinski, Radomir Gono, Elzbieta Jaisinski, Vadim Bolshev, “Prediction of Chronic Kidney Disease - A Machine Learning perspective", IEEE Access, 9: 17312-17334,2021
46. Akhilesh Kumar Sharma, Gaurav Aggarwal, Sachit Bhardwaj, Prasun Chakrabarti, Tulika Chakrabarti, Jemal Hussain, Siddhartha Bhattarcharyya, Richa Mishra, Anirban Das, Hairulnizam Mahdin, “Classification of Indian Classical Music with Time-Series Matching using Deep Learning”, IEEE Access, 9: 102041-102052, 2021.
47. Abrar Ahmed Chhipa , Vinod Kumar, R. R. Joshi, Prasun Chakrabarti, Michal Jaisinski, Alessandro Burgio, Zbigniew Leonowicz, Elzbieta Jasinska, Rajkumar Soni, Tulika Chakrabarti, “Adaptive Neuro-fuzzy Inference System Based Maximum Power Tracking Controller for Variable Speed WECS”, Energies ,14(19) :6275, 2021.
48. Tulika Chakrabarti, Sibabrata Mukhopadhyay, Prasun Chakrabarti, Gholamreza Hatam, Mohammad Nami, “Phenyl Ethanoid Glycoside from the bark of Oroxylum indicum vent: a potential inhibitor of DNA Topoisomerase IB of Leismania donovani”, Journal of Advanced Medical Sciences and Applied Technologies , 2021.
49. Sreemoy Kanti Das, GS Chakraborthy, Tulika Chakrabarti, Prasun Chakrabarti, Mohammad Javad Gholamzadeh, Mohammad Nami, “Evaluation of nootropic activity of standardized Epipremnum aureum extract against scopolamine-induced amnesia in experimental animals”, Journal of Advanced Medical Sciences and Applied Technologies, 6(1): 64-71,2021
50. Prasun Chakrabarti, Tulika Chakrabarti, Mayank Sharma., D Atre D, K.Baba Pai, “Quantification of Thought Analysis of Alcohol-addicted persons and memory loss of patients suffering from stage-4 liver cancer”, Advances in Intelligent Systems and Computing, 1053, pp.1099-1105, 2020
51. Prasun Chakrabarti, Tulika Chakrabarti, Biswajit Satpathy, I SenGupta, Jonathan Andrew Ware, “Analysis of strategic market management in the light of stochastic processes, recurrence relation, Abelian group and expectation”, Advances in Artificial Intelligence and Data Engineering, 1133, pp.701-710, 2020
52. Prasun Chakrabarti, Siddhant Bane, Biswajit Satpathy, Mark Goh, B N Datta, Tulika Chakrabarti, “Compound Poisson Process and its Applications in Business”, Lecture Notes in Electrical Engineering, 601, pp.678-685,2020
53. Prasun Chakrabarti, Biswajit Satpathy, Siddhant Bane, Tulika Chakrabarti, N S Chaudhuri, Pierluigi Siano , “Business forecasting in the light of statistical approaches and machine learning classifiers”, Communications in Computer and Information Science , 1045, pp.13-21, 2019
54. Manish Tiwari, Prasun Chakrabarti, Tulika Chakrabarti, “Novel work of diagnosis in liver cancer using Tree classifier on liver cancer dataset (BUPA liver disorder)”, Communications in Computer and Information Science, 837, pp.155-160, 2018
55. Manish Tiwari, Prasun Chakrabarti, Tulika Chakrabarti, “Performance analysis and error evaluation towards the liver cancer diagnosis using lazy classifiers for ILPD”, Communications in Computer and Information Science, 837, pp.161-168,2018
56. Prasun Chakrabarti, Manish Tiwari, Tulika Chakrabarti, “Performance Vector analysis in context to liver cancer-A Support Vector Machine Approach with a survey on the latest Perspectives of Chemistry in liver cancer treatment”, International Journal of Computer Science and Information Security, 14(9):1238,2016
57. A. Uthiramoorthy, A. Bhardwaj, J. Singh, K. Pant, M. Tiwari and J. L. A. Gonzáles, "A Comprehensive review on Data Mining Techniques in managing the Medical Data cloud and its security constraints with the maintained of the communication networks," 2023 International Conference on Artificial Intelligence and Smart Communication (AISC), Greater Noida, India, 2023, pp. 618-623.
58. D. S. Das, D. Gangodkar, R. Singh, P. Vijay, A. Bhardwaj and A. Semwal, "Comparative Analysis of Skin Cancer Prediction using Neural Networks and Transfer Learning," 2022 5th International Conference on Contemporary Computing and Informatics (IC3I), Uttar Pradesh, India, 2022, pp. 367-371.
59. A. Chaturvedi, A. Bhardwaj, D. Singh, B. Pant, J. L. A. Gonzáles and F. A., "Integration of DL on Multi-Carrier Non-Orthogonal Multiple Access System with Simultaneous Wireless Information and Power Transfer," 2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART), Moradabad, India, 2022, pp. 640-643.
60. Praveen Kumar Sharma, Sushil Sharma, Common fixed point for weakly compatible maps in intuitionistic fuzzy metric spaces using property (S-B)”, Journal of Non-linear Analysis Optimization and Theory, Vol 5, No.2 (2014), 105-117.
61. Praveen Kumar Sharma, Sushil Sharma, Common fixed-point theorem in intuitionistic fuzzy metric space under strict contractive conditions", Journal of Non-linear Analysis Optimization and Theory Vol 3 No.2 (2012), 161-169.
62. Praveen Kumar Sharma, Common fixed points for weakly compatible maps in intuitionistic fuzzy metric spaces using the property (CLRg)”, International Knowledge Press, Asian Journal of Mathematics & Computer Research, Vol 6, No.2 (2015), 138-150.
63. Praveen Kumar Sharma, Shivram Sharma, Common Fixed-Point Theorems for Six Self Maps in FM-Spaces Using Common Limit in Range Concerning Two Pairs of Products of Two Different Self-maps”, Revista Geintec-Gestao Inovacao E Tecnologias, Vol 11, No. 4 (2021), 5634-5642.
64. Shivam Sharma, Praveen Kumar Sharma,A study of SIQR model with Holling type–II incidence rate”, Malaya Journal of Matematik, Vol. 9, No. 1, 305-311.
65. J. J. Patil, Y. H. Patil, A. Ghosh, “Comprehensive and analytical review on optical fiber refractive index sensor”, 2020 4th International Conference on Trends in Electronics and Informatics (ICOEI) (48184), IEEE, P. 169-175, June. 15, 2020.
66. H. Bohra, A. Ghosh, “Design and analysis of microstrip low pass and band stop filters”, International Journal of Recent Technology and Engineering (IJRTE), Vol. 8, Issue 3, P. 6944-6951, Sept. 2019.
67. Y. H. Patil, A. Ghosh, “Optical fiber humidity sensors: a review”, 2020 4th International Conference on Trends in Electronics and Informatics (ICOEI) (48184), IEEE, P. 207-213, June. 15, 2020.
68. J. J. Patil, Y. H. Patil, A. Ghosh, “Fiber Optics Refractive Index Sensor based on Intensity Modulation”, 2020 4th International Conference on Electronics, Communication and Aerospace Technology (ICECA), IEEE, P. 623-628, May. 2020.
69. H. Bohra, A. Ghosh, A. Bhaskar, A. Sharma, “A miniaturized notched band microstrip wideband filter with hybrid defected ground structure technique”, 2020 Third International Conference on Smart Systems and Inventive Technology (ICSSIT), IEEE, P. 745-750, Aug. 2020.
70. Y. H. Patil, J. J. Patil, A. Gaikwad, A. Ghosh, “Development of Optical Fiber Test Bench for Intensity-Modulated Optical Fiber Sensors”, 2020 4th International Conference on Trends in Electronics and Informatics (ICOEI) (48184), IEEE, P. 176-180, June. 2020.
71. H. Bohra, A. Ghosh, “A Review on Different Optimization Techniques for Selecting Optimal Parameters in Microstrip Bandpass Filter Design”, International Journal of Advanced Science and Technology, Vo. 28, Issue 14, P. 379-394, Nov. 2019.
72. J. Terdale, A. Ghosh, “An intensity-modulated optical fiber sensor with agarose coating for measurement of refractive index”, International Journal of System Assurance Engineering and Management, Springer India, P. 1-7, Nov. 2022.
73. J. J. Patil, A. Ghosh, “Intensity Modulation based U shaped Plastic Optical Fiber Refractive Index Sensor” 2022 6th International Conference on Trends in Electronics and Informatics (ICOEI), IEEE, P. 18-24, Apr. 2022.
74. H. Bohra, A. Ghosh, A. Bhaskar, “Design and Analysis of Spurious Harmonics Suppressed Microstrip Ultrawide Band Filter using Modified Defected Ground Structure Techniques”, Wireless Personal Communications, Springer US, Vol. 121, Issue 1, P. 361-380, Nov. 2021.
75. H. Bohra, A. Ghosh, A. Bhaskar, A. Sharma, “A Miniaturized Ultra-Wideband Low-Pass Microstrip Filter Design using Modified Defected Ground Structure Techniques”, Invertis University, Vol. 14, Issue 1, P. 25-30, 2021.
76. A. Ghosh, P. Chakrabarti, P. Siano, “Approach towards realizing the Security Threats for Mobile IPv6 and Solution Thereof”, International Journal of Computer Applications, Foundation of Computer Science, Vol. 90, Issue 10, Jan. 2014.
77. A. Ghosh, P. Chakrabarti, D. Bhatnagar, “Performance Evaluation of Optimized Mobile IP Protocol Vis-à-vis Bit Map Indexing Method”, International Journal of Computer Applications, Foundation of Computer Science, Vol. 75, Issue: 2, Jan. 2013.
78. H. Patidar, P. Chakrabarti, A. Ghosh, “Parallel Computing Aspects in Improved Edge Cover Based Graph Coloring Algorithm”, Indian Journal of Science and Technology, Vol. 10, P. 25, Jul. 2017.
79. Kaur, L., & Shah, S. (2022). Production of bacterial cellulose by Acetobacter tropicalis isolated from decaying apple waste. Asian Journal of Chemistry, 34(2), 453–458.
80. Kaur, L., & Shah, S. (2022). Screening and characterization of cellulose-producing bacterial strains from decaying fruit waste. International Journal of Food and Nutritional Science, 11, 8–14.
81. Verma,S & Kaur,L. . (2018). Identification Of Waste Utilizing Bacteria from Fruit Waste. Global Journal for Research Analysis Volume-7(6, June)
82. Kaur, L., & Singh, N., Effect of mustard oil and process variables extrusion behavior of rice grits (2000). Journal Of Food Science and Technology. Mysore, 37, 656–660.
83. Thapar, Lakhvinder. (2017). Bulk And Nano-Zinc Oxide Particles Affecting Physio-Morphological Properties of Pisum Sativum. International Journal of Research in Engineering and Applied Sciences (IJREAS).
84. Mathew, Sneha & Thapar, Lakhvinder. (2019). Estimation of Protein Intake on the Basis of Urinary Urea Nitrogen in Patients with Non-Alcoholic Fatty Liver. International Journal for Research in Applied Science and Engineering Technology. 7. 2321-9653.
85. Thapar, Lakhvinder. (2017). Fermentation Potential of Prebiotic Juice Obtained from Natural Sources. International Journal of Advanced Research. 5. 1779-1785.
86. Mittal, Srishty & Thapar, Lakhvinder. (2019). Vitamin D Levels Between the Tuberculosis Infected and Non –Infected Subjects In 16-25 Years of Age.
87. V. Bansal, S. Pandey, S. K. Shukla, D. Singh, S. A. Rathod and J. L. A. Gonzáles, "A Frame Work of Security Attacks, Issues Classifications and Configuration Strategy for IoT Networks for the Successful Implementation," 2022 5th International Conference on Contemporary Computing and Informatics (IC3I), Uttar Pradesh, India, 2022, pp. 1336-1339.
88. V. Gunturu, V. Bansal, M. Sathe, A. Kumar, A. Gehlot and B. Pant, "Wireless Communications Implementation Using Blockchain as Well as Distributed Type of IOT," 2023 International Conference on Artificial Intelligence and Smart Communication (AISC), Greater Noida, India, 2023, pp. 979-982.
89. V. Suthar, V. Bansal, C. S. Reddy, J. L. A. Gonzáles, D. Singh and D. P. Singh, "Machine Learning Adoption in Blockchain-Based Smart Applications," 2022 5th International Conference on Contemporary Computing and Informatics (IC3I), Uttar Pradesh, India, 2022, pp. 372-378.
90. D. Uike, S. Agarwalla, V. Bansal, M. K. Chakravarthi, R. Singh and P. Singh, "Investigating the Role of Block Chain to Secure Identity in IoT for Industrial Automation," 2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART), Moradabad, India, 2022, pp. 837-841.
91. S. Sonnad, M. Sathe, D. K. Basha, V. Bansal, R. Singh and D. P. Singh, "The Integration of Connectivity and System Integrity Approaches using Internet of Things (IoT) for Enhancing Network Security," 2022 5th International Conference on Contemporary Computing and Informatics (IC3I), Uttar Pradesh, India, 2022, pp. 362-366.
92. Pooja Chopra, N. Junath, Sitesh Kumar Singh, Shakir Khan, R. Sugumar, Mithun Bhowmick, "Cyclic GAN Model to Classify Breast Cancer Data for Pathological Healthcare Task", BioMed Research International, vol. 2022, Article ID 6336700, 12 pages, 2022.
93. Khan, S. (2016). How Data Mining Can Help Curb City Crime. International Journal of Control Theory and Applications (IJCTA), 9(23), 483-488.
94. AlAjmi, M., & Khan, S. (2013). Mobile Community Networks Information Investigation for Additional Significance. Paper presented at the ICERI2013 Proceedings.
95. Khan, S. (2021). Data Visualization to Explore the Countries Dataset for Pattern Creation. International Journal of Online Biomedical Engineering, 17(13), 4-19.
96. Khan, S. (2021). Study Factors for Student Performance Applying Data Mining Regression Model Approach. International Journal of Computer Science Network Security, 21(2), 188-192.
97. AlAjmi, M., & Khan, S. (2015). Part of Ajax and Openajax in Cutting Edge Rich Application Advancement For E-Learning. Paper presented at the INTED2015 Proceedings.
98. Khan, S., & Alfaifi, A. (2020). Modeling of Coronavirus Behavior to Predict It’s Spread. International Journal of Advanced Computer Science Applications, 11(5), 394-399.
99. Khan, S. (2020). Artificial Intelligence Virtual Assistants (Chatbots) are Innovative Investigators. International Journal of Computer Science Network Security, 20(2), 93-98.
100. Gupta, G., Khan, S., Guleria, V., Almjally, A., Alabduallah, B. I., Siddiqui, T., Albahlal, B. M., et al. (2023). DDPM: A Dengue Disease Prediction and Diagnosis Model Using Sentiment Analysis and Machine Learning Algorithms. Diagnostics, 13(6), 1093.
101. Khan, S., & Alshara, M. (2019). Development of Arabic evaluations in information retrieval. International Journal of Advanced Applied Sciences, 6(12), 92-98.
102. Fazil, M., Khan, S., Albahlal, B. M., Alotaibi, R. M., Siddiqui, T., & Shah, M. A. (2023). Attentional Multi-Channel Convolution with Bidirectional LSTM Cell Toward Hate Speech Prediction. IEEE Access, 11, 16801-16811.
103. Khan, S., AlAjmi, M., & Sharma, A. (2012). Safety Measures Investigation in Moodle LMS. Special Issue of International Journal of Computer Applications, ICNICT (4), 41-44.
104. AlAjmi, M., & Shakir, K. (2013). Data Mining in Learning Management System utilizing Moodle. Paper presented at the INTED2013 Proceedings.
105. AlAjmi, M., & Khan, S. (2012). The Utility of New Technologies in Enhancing Learning Vigilance in Educationally Poor Populations. Paper presented at the EDULEARN12 Proceedings.
106. Khan, S., AlAjmi, D. M., Sarwar, A., & Akhtar, A. (2013). Keeping Data on Clouds: Cloud Computing Significance. International Journal of Engineering Science Research IJESR, 3(3).
107. AlAjmi, M., & Khan, S. (2012). Data Mining–Based, Service Oriented Architecture (SOA) In E-Learning. Paper presented at the Iceri2012 Proceedings.
108. Alajmi, M., & Khan, S. (2011). Effective Use of Web 2.0 Tools in Pharmacy Students'clinical Skills Practice During Field Training. Paper presented at the iceri2011 proceedings.
109. Khan, S. (2017). An Inter-Operability and Open-Source Problem for Integrated Library System (Koha) and Digital Library (Dspace) As Single System. Paper presented at the Edulearn17 Proceedings.
110. Khan, S. (2018). Modern Internet of Things as a Challenge for Higher Education. International Journal of Computer Science Network Security, 18(12), 34-41.
111. Salehi, A. W., Khan, S., Gupta, G., Alabduallah, B. I., Almjally, A., Alsolai, H., Siddiqui, T., et al. (2023). A Study of CNN and Transfer Learning in Medical Imaging: Advantages, Challenges, Future Scope. Sustainability, 15(7), 5930.
112. Shaikh Abdul Hannan, “Development of Digital Transformation in Higher Education Institutions”, Journal of Computer Science & Computational Mathematics, Volume 13, Issue 01, pp 1-8, March 2023.
113. Shaikh Abdul Hannan, Pushparaj Pal, “Detection and classification of kidney disease using convolutional neural networks”, Journal of Neurology and Neurorehabilitation Research, Vol 8, Issue 2, pp 1-7, 2023.
114. Shaikh Abdul Hannan; Ms. Preeti Gupta; P. Vanitha; Rajesh Singh; Dimple Saini; Mohit Tiwari, “Analysis of blockchain technology based on digital management systems and data mining technology”, IEEE Xplore, 22 March 2023.
115. Heena Vig, Shaikh Abdul Hannan, Asok Kumar, Rajshree Singh, Juhi Juwairiyaah, Neen Kuriakose, “Gender and Age Classification Enabled Blockchain Security Mechanism for assisting Mobile Application, IEEE Xplore, 22nd March 2023.
116. Shaikh Abdul Hannan, “A Blockchain Technology to secure electronic Health Records in Healthcare System, London Journal of Research in Computer Science and Technology, Vol 23, Issue 1, PP 1-13, London Journal Press, 10 Feb 2023.
117. Shaikh Abdul Hannan, An Examination of the Blockchain Technology: Challenges and Future Opportunities, International Journal Of Engineering And Computer Science, Volume11 Issue 09 November2022, Page No.25612-25619.
118. Shaikh Abdul Hannan, “Application and Scope of Blockchain in Technical Research and Higher Education” Vol 20, Issue 15, page 6185-6191, NeuroQuantology, Nov 2022.
119. Shaikh Abdul Hannan, Manjusha Hivre, Lata, M., Krishna, B. H., Sathyasiva, S., & Arshad, M. W. “Brain damage detection using Machine learning approach”, International Journal of Health Sciences, Special Issue VIII, 27 Sept. 2022, PP 4910-4924.
120. Dubey, A., Mujoo, Shaikh Abdul Hannan., Satpathy, G., Arshad, M. W., & Manikandan, E., “Cancer detection using RNA sequencing and deep learning”, International Journal of Health Sciences, Special Issue VIII, 27 Sept. 2022, PP 4925-4939.
121. Arun Prasad, Shaikh Abdul Hannan, Kavita Panjwani, Muthe Ramu, Kawaender Singh Sidhu, Nagabhusanam Tida, “Detailed Investigation of the role of Artificial Intelligence in stock market predictions, British Journal of Administrative Management, Vol 58, Issue 06, 6th Sept 2022, UK.
122. E. Vashishtha, Effects of Maternal Smoking on Fetus and Child Development: a literature review, International Research Journal of Natural and Applied Sciences, Volume 6, Issue 1, Pages 92-107, 2019.
123. J. Kumar, K. Pal, S. N. Mahapatra, and S. S. Kundu, “Altman’s model for predicting business failure: case study of HAFED,” Abhigyan, vol. 29, no. 3, pp. 52–62, Oct. 2011.
124. D. J. Kumar, “Synoptic View on Economic Value Added (EVA) – Literature Review Summary” Wealth: JMBF, vol.5, no.2 pp. 34-57, 2016.
125. J. Kumar, “Evaluating Superiority of Modern Vis-A-Vis Traditional Financial Performance Measures: Evidences from Indian Pharmaceutical Industry,” JIMS8M: Jour. of Indian Manage. & Strat., vol. 21, no. 1, pp. 21, 2016.
126. J. Kumar, and Neha, “Patient Satisfaction in Out Patient Departments (OPDs): An Investigative Study in Government Hospitals of Haryana - ProQuest.” AAYAM: AKGIM Journal of Management, vol.6, no. 2, pp. 8-15, Jul-Dec. 2016
127. J. Kumar and R. Swami, “Professional Reformation of Business: The Case of an Existing Family Business,” DAMJ. Vol. 8, no.2 Mar-Sept. 2017.
128. J. Kumar, “Behavioural Finance - Literature Review Summary and Relevant Issues - ProQuest.” vol.9 no.1, pp 42-53, Jan-Jun, 2019.
129. J. Kumar and G. Bansal, “Impact of Financial Literacy (Fl) And Access to Banking Services (Ac) On Financial Well-Being (Fwb): An Empirical Study,” IJM, vol. 11, no. 12, Dec. 2020.
130. J. Kumar and N. Prince, “Overconfidence bias in the Indian stock market in diverse market situations: an empirical study,” Int J Syst Assur Eng Manag, vol. 13, no. 6, pp. 3031–3047, Dec. 2022.
131. J. Kumar and Anjali, “Role of the Internet of Things (IoT) in Digital Financial Inclusion,” in IoT Based Smart Applications, N. Sindhwani, R. Anand, M. Niranjanamurthy, D. Chander Verma, and E. B. Valentina, Eds., in EAI/Springer Innovations in Communication and Computing. Cham: Springer International Publishing, 2023, pp. 363–373.
132. J. Kumar and V. Rani, “Journey of Financial Technology (FinTech): A Systematic Literature Review and Future Research Agenda,” in Exploring the Latest Trends in Management Literature, S. Rana, Sakshi, and J. Singh, Eds., in Review of Management Literature, vol. 1. Emerald Publishing Limited, 2022, pp. 89–108.
133. J. Kumar, V. Rani, G. Rani, and T. Sarker, “Determinants of the financial wellbeing of individuals in an emerging economy: an empirical study,” International Journal of Bank Marketing Mar. 2023.
134. D. Saxena, "A Non-Contact Based System to Measure SPO2 and Systolic/Diastolic Blood Pressure using Rgb-Nir Camera." Order No. 29331388, The University of Texas at Arlington, United States -- Texas, 2022.
135. Rathi, S., Chaturvedi, S., Abdullah, S., Rajput, G., Alqahtani, N. M., Chaturvedi, M., Gurumurthy, V., Saini, R., Bavabeedu, S. S., & Minervini, G. (2023). Clinical Trial to Assess Physiology and Activity of Masticatory Muscles of Complete Denture Wearer Following Vitamin D Intervention. Medicina, 59(2), 410.
136. Kaur, K., Suneja, B., Jodhka, S., Saini, R. S., Chaturvedi, S., Bavabeedu, S. S., Alhamoudi, F. H., Cicciù, M., & Minervini, G. (2023). Comparison between Restorative Materials for Pulpotomised Deciduous Molars: A Randomized Clinical Study. Children, 10(2), 284.
137. Kumar A, Saini RS, Sharma V, Rai R U, Gupta P, Sabharwal P (2021), Assessment of Pattern of Oral Prosthetic Treatment and Prevalence of Oral Diseases in Edentulous Patients in North Indian Population: A Cross-sectional Study. J Pharm Bioallied Sci. 2021 Jun; 13(Suppl 1): S187–S189.
138. Solanki, J., Jain, R., Singh, R., Gupta, S., Arya, A., & Tomar, D. (2015). Prevalence of Osteosclerosis Among Patients Visiting Dental Institute in Rural Area of Western India. Journal of clinical and diagnostic research: JCDR, 9(8), ZC38–ZC40.
139. Alshadidi, A. A. F., Alshahrani, A. A., Aldosari, L. I. N., Chaturvedi, S., Saini, R. S., Hassan, S. A. B., Cicciù, M., & Minervini, G. (2023). Investigation on the Application of Artificial Intelligence in Prosthodontics. Applied Sciences, 13(8), 5004.
140. Mohamed J. Saadh, Andrés Alexis Ramírez-Coronel, Ravinder Singh Saini, José Luis Arias-Gonzáles, Ali H. Amin, Juan Carlos Orosco Gavilán & Ioan Sârbu (2023) Advances in mesenchymal stem/stromal cell-based therapy and their extracellular vesicles for skin wound healing.Human Cell (2023).
141. A. R. Yeruva and V. B. Ramu, “Optimising AIOps system performance for e-commerce and online retail businesses with the ACF model,” Int. J. Intellect. Prop. Manag., vol. 1, no. 1, p. 1, 2022.
142. V. B. Ramu and A. R. Yeruva, “AIOps research innovations, performance impact and challenges faced,” Int. J. Syst. Syst. Eng., vol. 13, no. 3, p. 1, 2023.
143. A. Khelifi, A. Abran, and L. Buglione, "2.4 a system of reference for software measurements with ISO 19761 (COSMIC FFP)," in COSMIC Function Points: Theory and Advanced Practices, vol. 142, 2016.
144. A. Khelifi and A. Abran, "Design steps for developing software measurement standard etalons for iso 19761 (cosmic-ffp)," in WSEAS International Conference on COMPUTERS, 2007.
145. M. A. Talib, A. Khelifi, A. Abran, and O. Ormandjieva, "Techniques for quantitative analysis of software quality throughout the sdlc: The swebok guide coverage," in 2010 Eighth ACIS International Conference on Software Engineering Research, Management and Applications, pp. 321-328, 2010.
146. M. A. Talib, A. Khelifi, and T. Ugurlu, "Using ISO 27001 in teaching information security," in IECON 2012-38th Annual Conference on IEEE Industrial Electronics Society, pp. 3149-3153, 2012.
147. M. Aburrous and A. Khelifi, "Phishing detection plug-in toolbar using intelligent Fuzzy-classification mining techniques," in the international conference on soft computing and software engineering [SCSE’13], San Francisco State University, San Francisco, California, USA, 2013.
148. A. Khelifi, Y. Grisi, D. Soufi, D. Mohanad, and P. V. S. Shastry, "M-Vote: a reliable and highly secure mobile voting system," in 2013 Palestinian International Conference on information and communication technology, pp. 90-98, 2013.
149. A. Khelifi, M. Aburrous, M. A. Talib, and P. V. S. Shastry, "Enhancing protection techniques of e-banking security services using open-source cryptographic algorithms," in 2013 14th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, pp. 89-95, 2013.
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Published
2023-06-26
How to Cite
S. Suman Rajest, S. Silvia Priscila, R. Regin, Shynu T, & Steffi. R. (2023). Application of Machine Learning to the Process of Crop Selection Based on Land Dataset. International Journal on Orange Technologies, 5(6), 91-112. Retrieved from https://journals.researchparks.org/index.php/IJOT/article/view/4546
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Articles
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