{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T07:17:09Z","timestamp":1777706229582,"version":"3.51.4"},"reference-count":45,"publisher":"SAGE Publications","issue":"4","license":[{"start":{"date-parts":[[2025,8,8]],"date-time":"2025-08-08T00:00:00Z","timestamp":1754611200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Intelligent &amp; Fuzzy Systems: Applications in Engineering and Technology"],"published-print":{"date-parts":[[2026,4]]},"abstract":"<jats:p>\n                    Cultivating red chili or Capsicum annuum is important in agriculture in terms of the economy and food. However, the disease known as the yellow virus, which is transmitted through a vector, has caused enormous losses in crops, requiring new advanced predictive models for the control of new diseases. Most of these conventional numerical methods could not effectively capture the non-linear dynamics of disease transmission; therefore, more research is needed on computational approaches. This optimization study aims to create a stochastic modeling framework with Levenberg-Marquardt backpropagation neural networks (LMB) to improve the precision of the prediction of the spread of the yellow virus in chili crops. The new model of the LMB neural network was trained and validated against numerical solutions using the Adam solver. The model minimizes the mean square error (MSE) to be\n                    <jats:inline-formula>\n                      <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" display=\"inline\" overflow=\"scroll\">\n                        <mml:mn>1.54<\/mml:mn>\n                        <mml:mo>\u00d7<\/mml:mo>\n                        <mml:msup>\n                          <mml:mn>10<\/mml:mn>\n                          <mml:mrow>\n                            <mml:mo>\u2212<\/mml:mo>\n                            <mml:mn>11<\/mml:mn>\n                          <\/mml:mrow>\n                        <\/mml:msup>\n                      <\/mml:math>\n                    <\/jats:inline-formula>\n                    to mark its highly accurate predictability. Shows a regression analysis of a correlation coefficient\n                    <jats:inline-formula>\n                      <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" display=\"inline\" overflow=\"scroll\">\n                        <mml:mi>R<\/mml:mi>\n                        <mml:mo>&gt;<\/mml:mo>\n                        <mml:mn>0.99<\/mml:mn>\n                      <\/mml:math>\n                    <\/jats:inline-formula>\n                    , which confirms it to be a reliable prediction. In addition, stability analysis according to the basic reproduction number\n                    <jats:inline-formula>\n                      <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" display=\"inline\" overflow=\"scroll\">\n                        <mml:msub>\n                          <mml:mi>R<\/mml:mi>\n                          <mml:mn>0<\/mml:mn>\n                        <\/mml:msub>\n                      <\/mml:math>\n                    <\/jats:inline-formula>\n                    is performed to evaluate the dynamics of disease spread. It is proven that the bona fide LMB neural network surpasses numerical methods or traditional solvers in efficiency in computation and accuracy and hence can be considered a precious asset in real-time forecasting of crops or plant diseases. It also demonstrates a bright future for neural networks in plant disease modeling. It can practically move into data-driven precision agriculture, optimize pest control measures, and promote sustainable crop management strategies.\n                  <\/jats:p>","DOI":"10.1177\/18758967251358113","type":"journal-article","created":{"date-parts":[[2025,8,8]],"date-time":"2025-08-08T07:44:52Z","timestamp":1754639092000},"page":"1154-1172","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Decoding Yellow Virus Dynamics in Chili Crops: A Stochastic Approach Using Neural Networks"],"prefix":"10.1177","volume":"50","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2409-6513","authenticated-orcid":false,"given":"N Seshagiri","family":"Rao","sequence":"first","affiliation":[{"name":"Department of Mathematics and Statistics, Vignan\u2019s Foundation for Science, Technology and Research, Guntur, Andhra Pradesh, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9016-322X","authenticated-orcid":false,"given":"G Srinivasa","family":"Rao","sequence":"additional","affiliation":[{"name":"Department of Mathematics and Statistics, Vignan\u2019s Foundation for Science, Technology and Research, Guntur, Andhra Pradesh, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7453-9357","authenticated-orcid":false,"given":"Debnarayan","family":"Khatua","sequence":"additional","affiliation":[{"name":"Department of Mathematics and Statistics, Vignan\u2019s Foundation for Science, Technology and Research, Guntur, Andhra Pradesh, India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2025,8,8]]},"reference":[{"key":"e_1_3_2_2_1","unstructured":"AlAVO T. B. (2015). The insect pathogenic fungus verticillium lecanii (zimm.) viegas and its use for pests control: A review."},{"key":"e_1_3_2_3_1","doi-asserted-by":"publisher","DOI":"10.1080\/713710567"},{"key":"e_1_3_2_4_1","article-title":"A radial basis neural network for the hard water consumption with kidney model","author":"Alderremy A.","year":"2024","unstructured":"Alderremy A., Hernandez-Castaneda D., Gomez-Aguilar J., Sabir, Z., Aly, S., & Lavin-Delgado, J. E. (2024). A radial basis neural network for the hard water consumption with kidney model. International Journal of Geometric Methods in Modern Physics.\u00a0https:\/\/doi.org\/10.1142\/S0219887825500902","journal-title":"International Journal of Geometric Methods in Modern Physics"},{"key":"e_1_3_2_5_1","doi-asserted-by":"crossref","unstructured":"Amelia R. Anggriani N. Istifadah N. & Supriatna A. K. (2021). Stability analysis for yellow virus disease mathematical model of red chili plants. In Journal of Physics: Conference Series\u00a0(volume 1722 p. 012043). IOP Publishing.","DOI":"10.1088\/1742-6596\/1722\/1\/012043"},{"key":"e_1_3_2_6_1","first-page":"351","article-title":"Optimal control model of verticillium lecanii application in the spread of yellow red chili virus","volume":"18","author":"Amelia R.","year":"2019","unstructured":"Amelia R., Anggriani N., Supriatna A. (2019). Optimal control model of verticillium lecanii application in the spread of yellow red chili virus. WSEAS Transactions on Mathematics, 18, 351\u2013358.","journal-title":"WSEAS Transactions on Mathematics"},{"key":"e_1_3_2_7_1","doi-asserted-by":"crossref","unstructured":"Anggriani N. Mardiyah M. Istifadah N. & Supriatna A. K. (2018). Optimal control issues in plant disease with host demographic factor and botanical fungicides. In IOP conference series: Materials Science and Engineering (volume 332 p. 012036). IOP Publishing.","DOI":"10.1088\/1757-899X\/332\/1\/012036"},{"key":"e_1_3_2_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2024.107049"},{"key":"e_1_3_2_9_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00366-021-01406-7"},{"key":"e_1_3_2_10_1","doi-asserted-by":"publisher","DOI":"10.1002\/htj.22071"},{"issue":"10","key":"e_1_3_2_11_1","first-page":"2435","article-title":"Efficiency of the entomopathogenic fungus verticillium lecanii in the biological control of trialeurodes vaporariorum,(homoptera: Aleyrodidae), a greenhouse culture pest","volume":"6","author":"Bouhous M.","year":"2012","unstructured":"Bouhous M., Larous L. (2012). Efficiency of the entomopathogenic fungus verticillium lecanii in the biological control of trialeurodes vaporariorum,(homoptera: Aleyrodidae), a greenhouse culture pest. African Journal of Microbiology Research, 6(10), 2435\u20132442.","journal-title":"African Journal of Microbiology Research"},{"key":"e_1_3_2_12_1","doi-asserted-by":"publisher","DOI":"10.1155\/2010\/679613"},{"key":"e_1_3_2_13_1","doi-asserted-by":"publisher","DOI":"10.1080\/00207160.2024.2409794"},{"key":"e_1_3_2_14_1","doi-asserted-by":"publisher","DOI":"10.1007\/s40858-020-00365-6"},{"key":"e_1_3_2_15_1","doi-asserted-by":"crossref","unstructured":"Eastop V. (1977). Worldwide importance of aphids as virus vectors. In Aphids as virus vectors (pp. 3\u201362). Elsevier.","DOI":"10.1016\/B978-0-12-327550-9.50006-9"},{"key":"e_1_3_2_16_1","doi-asserted-by":"publisher","DOI":"10.1142\/S0218348X21400351"},{"key":"e_1_3_2_17_1","doi-asserted-by":"crossref","unstructured":"Hannum S.(2019). Begomovirus detection on diseased chili plant (Capsicum annum L.) in Tanah Karo North Sumatera with PCR techniques. In IOP Conference Series: Earth and Environmental Science volume 305. IOP Publishing p. 012057.","DOI":"10.1088\/1755-1315\/305\/1\/012057"},{"key":"e_1_3_2_18_1","doi-asserted-by":"publisher","DOI":"10.5994\/jei.15.2.87"},{"key":"e_1_3_2_19_1","doi-asserted-by":"publisher","DOI":"10.1111\/jen.12575"},{"key":"e_1_3_2_20_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijhydene.2020.11.097"},{"key":"e_1_3_2_21_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2020.106791"},{"key":"e_1_3_2_22_1","doi-asserted-by":"publisher","DOI":"10.17485\/ijst\/2015\/v8i13\/58749"},{"key":"e_1_3_2_23_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-019-04573-3"},{"key":"e_1_3_2_24_1","doi-asserted-by":"publisher","DOI":"10.12988\/ams.2014.4110"},{"key":"e_1_3_2_25_1","doi-asserted-by":"publisher","DOI":"10.18502\/kls.v2i1.184"},{"key":"e_1_3_2_26_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-020-05143-8"},{"key":"e_1_3_2_27_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2025.112997"},{"key":"e_1_3_2_28_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2025.109807"},{"key":"e_1_3_2_29_1","doi-asserted-by":"publisher","DOI":"10.1142\/S0218348X2140017X"},{"key":"e_1_3_2_30_1","doi-asserted-by":"publisher","DOI":"10.3389\/fphy.2020.00224"},{"key":"e_1_3_2_31_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.aej.2021.01.004"},{"key":"e_1_3_2_32_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.matcom.2021.02.004"},{"key":"e_1_3_2_33_1","doi-asserted-by":"publisher","DOI":"10.1007\/s40314-020-01350-0"},{"key":"e_1_3_2_34_1","doi-asserted-by":"publisher","DOI":"10.1140\/epjp\/s13360-020-00424-6"},{"key":"e_1_3_2_35_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.matcom.2020.06.021"},{"key":"e_1_3_2_36_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-020-05187-w"},{"key":"e_1_3_2_37_1","doi-asserted-by":"publisher","DOI":"10.1002\/htj.22010"},{"key":"e_1_3_2_38_1","doi-asserted-by":"publisher","DOI":"10.1007\/s13204-020-01581-x"},{"issue":"1","key":"e_1_3_2_39_1","first-page":"5251804","article-title":"Impact of activation energy and temperature-dependent heat source\/sink on maxwell\u2013sutterby fluid","volume":"2020","author":"Sajid T.","year":"2020","unstructured":"Sajid T., Tanveer S., Sabir Z., & Guirao, J. L. G. (2020). Impact of activation energy and temperature-dependent heat source\/sink on maxwell\u2013sutterby fluid. Mathematical Problems in Engineering, 2020(1), 5251804.","journal-title":"Mathematical Problems in Engineering"},{"key":"e_1_3_2_40_1","doi-asserted-by":"publisher","DOI":"10.1186\/1687-1847-2014-59"},{"key":"e_1_3_2_41_1","first-page":"1","article-title":"Modelling and analysis of a vector-host epidemic model with saturated incidence rate under treatment","volume":"4","author":"Sneha P.","year":"2015","unstructured":"Sneha P., Jain S., Khandewal R., & Ujjainkar, G. (2015). Modelling and analysis of a vector-host epidemic model with saturated incidence rate under treatment. International Journal of Applied Mathematics & Statistical Sciences (IJAMSS), 4, 1\u201316.","journal-title":"International Journal of Applied Mathematics & Statistical Sciences (IJAMSS)"},{"issue":"4","key":"e_1_3_2_42_1","first-page":"407","article-title":"Sensitivity estimates for nonlinear mathematical models","volume":"1","author":"Sobol I. M.","year":"1993","unstructured":"Sobol I. M. (1993). Sensitivity estimates for nonlinear mathematical models. Math Model Comput Exp, 1(4), 407\u2013414.","journal-title":"Math Model Comput Exp"},{"key":"e_1_3_2_43_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2019.105826"},{"key":"e_1_3_2_44_1","doi-asserted-by":"publisher","DOI":"10.1140\/epjp\/s13360-020-00557-8"},{"key":"e_1_3_2_45_1","doi-asserted-by":"publisher","DOI":"10.1140\/epjp\/s13360-020-00417-5"},{"key":"e_1_3_2_46_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2019.04.022"}],"container-title":["Journal of Intelligent &amp; Fuzzy Systems: Applications in Engineering and Technology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/18758967251358113","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.1177\/18758967251358113","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/18758967251358113","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T09:46:21Z","timestamp":1777455981000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.1177\/18758967251358113"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,8]]},"references-count":45,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2026,4]]}},"alternative-id":["10.1177\/18758967251358113"],"URL":"https:\/\/doi.org\/10.1177\/18758967251358113","relation":{},"ISSN":["1064-1246","1875-8967"],"issn-type":[{"value":"1064-1246","type":"print"},{"value":"1875-8967","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,8,8]]}}}