Granule-State Intelligent Mathematics for Analyzing Unseen Risks
An unseen risk (UR) means that there is miserly information about that risk. Traditional mathematical paradigms for risk analysis, especially probability models based on the law of large numbers, cannot analyze any UR. In this paper, we for the first time propose granule-state intelligent mathematic...
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Society for Risk Analysis - China
2024-12-01
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| Series: | Journal of Risk Analysis and Crisis Response (JRACR) |
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| Online Access: | https://doi.org/10.54560/jracr.v14i4.556 |
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| author | Chong-fu Huang Yun-dong Huang |
| author_facet | Chong-fu Huang Yun-dong Huang |
| author_sort | Chong-fu Huang |
| collection | DOAJ |
| description | An unseen risk (UR) means that there is miserly information about that risk. Traditional mathematical paradigms for risk analysis, especially probability models based on the law of large numbers, cannot analyze any UR. In this paper, we for the first time propose granule-state intelligent mathematics (GSIM) based on granules and states as basic elements. "Concept", "Knowledge", and "Consciousness" are referred to as granules in thinking activities. A certain situation in which a granule may change is called the state of that granule. Traditional mathematics is a special case of GSIM. All operations and models in traditional mathematics are operations and models in GSIM. In addition, the basic operations in GSIM should at least include averaging, cracking, interaction, stacking, and fusion. This paper discusses the granule-state diffusion model that achieves "drawing inferences about other cases from one instance" through mutual reference and uses this model to analyze again a case of death risk in a virtual city at the beginning of the corona virus disease 2019 (COVID-19) outbreak in March 2020. According to the diffusion model of GSIM, the possibility of "Significant Increase" in infection rate is 0.354, which is much higher than the possibility of "Stable" which is 0.131. It is inferred that within the next 30 days, in this city with a population of 10 million, the death toll of COVID-19 will exceed 189170, the result of analysis in 2020. It has been proven that the infection rate in uncontrolled areas has significantly increased since March 2020. The paper's core contribution is not in the suggested model, but the view of point that it is times to study IM for supporting artificial intelligence (AI). GSIM opened a narrow seam to show a new world, where AI supported by IM might have consciousness and will be smarter. |
| format | Article |
| id | doaj-art-8a3d5e13ee484ab29c7710bf87f04965 |
| institution | Kabale University |
| issn | 2210-8491 2210-8505 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Society for Risk Analysis - China |
| record_format | Article |
| series | Journal of Risk Analysis and Crisis Response (JRACR) |
| spelling | doaj-art-8a3d5e13ee484ab29c7710bf87f049652025-01-03T09:01:20ZengSociety for Risk Analysis - ChinaJournal of Risk Analysis and Crisis Response (JRACR)2210-84912210-85052024-12-01144-2423452https://doi.org/10.54560/jracr.v14i4.556Granule-State Intelligent Mathematics for Analyzing Unseen RisksChong-fu Huang0Yun-dong Huang1Academy of Disaster Risk Sciences, Faculty of Geographical Science, Beijing Normal University, Beijing (100875), ChinaThe Bill Munday School of Business, St. Edward's University, Austin, Texas (78704), USA; Correspondence: yhuang2@stedwards.eduAn unseen risk (UR) means that there is miserly information about that risk. Traditional mathematical paradigms for risk analysis, especially probability models based on the law of large numbers, cannot analyze any UR. In this paper, we for the first time propose granule-state intelligent mathematics (GSIM) based on granules and states as basic elements. "Concept", "Knowledge", and "Consciousness" are referred to as granules in thinking activities. A certain situation in which a granule may change is called the state of that granule. Traditional mathematics is a special case of GSIM. All operations and models in traditional mathematics are operations and models in GSIM. In addition, the basic operations in GSIM should at least include averaging, cracking, interaction, stacking, and fusion. This paper discusses the granule-state diffusion model that achieves "drawing inferences about other cases from one instance" through mutual reference and uses this model to analyze again a case of death risk in a virtual city at the beginning of the corona virus disease 2019 (COVID-19) outbreak in March 2020. According to the diffusion model of GSIM, the possibility of "Significant Increase" in infection rate is 0.354, which is much higher than the possibility of "Stable" which is 0.131. It is inferred that within the next 30 days, in this city with a population of 10 million, the death toll of COVID-19 will exceed 189170, the result of analysis in 2020. It has been proven that the infection rate in uncontrolled areas has significantly increased since March 2020. The paper's core contribution is not in the suggested model, but the view of point that it is times to study IM for supporting artificial intelligence (AI). GSIM opened a narrow seam to show a new world, where AI supported by IM might have consciousness and will be smarter.https://doi.org/10.54560/jracr.v14i4.556unseen riskartificial intelligencetraditional mathematicsintelligent mathematicsstream of consciousnessgranule-state diffusioncovid-19 |
| spellingShingle | Chong-fu Huang Yun-dong Huang Granule-State Intelligent Mathematics for Analyzing Unseen Risks Journal of Risk Analysis and Crisis Response (JRACR) unseen risk artificial intelligence traditional mathematics intelligent mathematics stream of consciousness granule-state diffusion covid-19 |
| title | Granule-State Intelligent Mathematics for Analyzing Unseen Risks |
| title_full | Granule-State Intelligent Mathematics for Analyzing Unseen Risks |
| title_fullStr | Granule-State Intelligent Mathematics for Analyzing Unseen Risks |
| title_full_unstemmed | Granule-State Intelligent Mathematics for Analyzing Unseen Risks |
| title_short | Granule-State Intelligent Mathematics for Analyzing Unseen Risks |
| title_sort | granule state intelligent mathematics for analyzing unseen risks |
| topic | unseen risk artificial intelligence traditional mathematics intelligent mathematics stream of consciousness granule-state diffusion covid-19 |
| url | https://doi.org/10.54560/jracr.v14i4.556 |
| work_keys_str_mv | AT chongfuhuang granulestateintelligentmathematicsforanalyzingunseenrisks AT yundonghuang granulestateintelligentmathematicsforanalyzingunseenrisks |