Deep Neural Networks for Curbing Climate Change-Induced Farmers-Herdsmen Clashes in a Sustainable Social Inclusion Initiative

dc.authorid Fernandez Sanz, Luis/0000-0003-0778-0073
dc.authorid AYENI, FOLUSO/0000-0003-0989-7056
dc.authorid Misra, Sanjay/0000-0002-3556-9331
dc.authorscopusid 56801895500
dc.authorscopusid 56962766700
dc.authorscopusid 25630384100
dc.authorscopusid 56495155400
dc.authorscopusid 6602627928
dc.authorscopusid 6603451290
dc.authorwosid Damaševičius, Robertas/E-1387-2017
dc.authorwosid Fernandez-Sanz, Luis/J-4895-2012
dc.authorwosid Ayeni, Foluso/IZE-2873-2023
dc.authorwosid Misra, Sanjay/K-2203-2014
dc.contributor.author Okewu, Emmanuel
dc.contributor.author Misra, Sanjay
dc.contributor.author Fernandez Sanz, Luis
dc.contributor.author Ayeni, Foluso
dc.contributor.author Mbarika, Victor
dc.contributor.author Damasevicius, Robertas
dc.contributor.other Computer Engineering
dc.contributor.other Computer Engineering
dc.date.accessioned 2024-10-06T10:58:07Z
dc.date.available 2024-10-06T10:58:07Z
dc.date.issued 2019
dc.department Atılım University en_US
dc.department-temp [Okewu, Emmanuel] Univ Lagos, Lagos, Nigeria; [Misra, Sanjay] Covenant Univ, Canaanland, Nigeria; [Misra, Sanjay] Atilim Univ, Ankara, Turkey; [Fernandez Sanz, Luis] Univ Alcala, Madrid, Spain; [Ayeni, Foluso; Mbarika, Victor; Damasevicius, Robertas] Southern Univ, Baton Rouge, LA USA; Kaunas Univ Technol, Kaunas, Lithuania en_US
dc.description Fernandez Sanz, Luis/0000-0003-0778-0073; AYENI, FOLUSO/0000-0003-0989-7056; Misra, Sanjay/0000-0002-3556-9331 en_US
dc.description.abstract Peaceful coexistence of farmers and pastoralists is becoming increasingly elusive and has adverse impact on agricultural revolution and global food security. The targets of Sustainable Development Goal 16 (SDG 16) include promoting peaceful and inclusive societies for sustainable development, providing access to justice for all and building effective, accountable and inclusive institutions at all levels. As a soft approach and long term solution to the perennial farmers herdsmen clashes with attendant humanitarian crisis, this study proposes a social inclusion architecture using deep neural network (DNN). This is against the backdrop that formulating policies and implementing programmes based on unbiased information obtained from historical agricultural data using intelligent technology like deep neural network (DNN) can be handy in managing emotions. In this vision paper, a DNN-based Farmers-Herdsmen Expert System (FHES) is proposed based on data obtained from the Nigerian National Bureau of Statistics for tackling the incessant climate change induced farmers-herdsmen clashes, with particular reference to Nigeria. So far, many lives have been lost. FHES is modelled as a deep neural network and trained using farmers-herdsmen historical data. Input variables used include land, water, vegetation, and implements while the output is farmers/herders disposition to peace. Regression analysis and pattern recognition performed by the DNN on the farmers-herdsmen data will enrich the inference engine of FHES with extracted rules (knowledge base). This knowledge base is then relied upon to classify future behaviours of herdsmen/farmers as well as predict their dispositions to violence. Critical stakeholders like governments, service providers and researchers can leverage on such advisory to initiate proactive and socially inclusive conflict prevention measures such as, people-friendly policies, programmes and legislations. This way, conflicts can be averted, national security challenges tackled, and peaceful atmosphere guaranteed for sustainable development. en_US
dc.description.woscitationindex Social Science Citation Index
dc.identifier.citationcount 11
dc.identifier.endpage 155 en_US
dc.identifier.issn 1895-6912
dc.identifier.issue 2 en_US
dc.identifier.scopus 2-s2.0-85070490132
dc.identifier.scopusquality Q3
dc.identifier.startpage 143 en_US
dc.identifier.uri https://hdl.handle.net/20.500.14411/8852
dc.identifier.volume 14 en_US
dc.identifier.wos WOS:000472684600014
dc.identifier.wosquality Q4
dc.institutionauthor Mısra, Sanjay
dc.institutionauthor Mısra, Sanjay
dc.language.iso en en_US
dc.publisher Politechnika Lubelska en_US
dc.relation.ispartof Problemy Ekorozwoju en_US
dc.relation.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.scopus.citedbyCount 16
dc.subject climate change en_US
dc.subject deep neural network en_US
dc.subject farmers-herdsmen clashes en_US
dc.subject policies and programmes en_US
dc.subject social inclusion en_US
dc.title Deep Neural Networks for Curbing Climate Change-Induced Farmers-Herdsmen Clashes in a Sustainable Social Inclusion Initiative en_US
dc.title.alternative Wykorzystanie głębokich sieci neuronowych w ograniczaniu zmian klimatycznych związanych z konfliktem farmerów i pasterzy w ramach inicjatywy na rzecz zrównoważonej integracji społecznej en_US
dc.type Article en_US
dc.wos.citedbyCount 11
dspace.entity.type Publication
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relation.isOrgUnitOfPublication.latestForDiscovery e0809e2c-77a7-4f04-9cb0-4bccec9395fa

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