Pub Date : 2023-04-15DOI: 10.31181/dmame0321052022v
Ashutosh Verma, S. Tripathy, D. Singhal
Warehouse management is the key aspect for an uninterrupted flow of products within a supply chain. This paper deals with the critical factors that are responsible for creating an impactful influence on the working of warehouse management. The analysis involves the selection of critical factors then applying Interpretive Structural Modelling (ISM) methodology to them in order to get the level partition and final ISM model. This research also involves the MICMAC analysis on the factors which classifies all the selected factors into four groups namely, autonomous variables, dependent variables, linkage variables and driver variables. This research will help the supply chain architects to establish a better and reliable warehouse system. As this research involves analysis of multiple domains that is why a variety of users can refer to this work for their businesses, also the ISM approach gives a good accuracy of the hierarchy of the factors which helps in deciding the most effective chronology of the implementation of various warehousing operations. Researchers can also refer to this work to get insights of the significance of warehouse management in the supply chain and also the complete working of the ISM methodology.
{"title":"The significance of warehouse management in supply chain: An ISM approach","authors":"Ashutosh Verma, S. Tripathy, D. Singhal","doi":"10.31181/dmame0321052022v","DOIUrl":"https://doi.org/10.31181/dmame0321052022v","url":null,"abstract":"Warehouse management is the key aspect for an uninterrupted flow of products within a supply chain. This paper deals with the critical factors that are responsible for creating an impactful influence on the working of warehouse management. The analysis involves the selection of critical factors then applying Interpretive Structural Modelling (ISM) methodology to them in order to get the level partition and final ISM model. This research also involves the MICMAC analysis on the factors which classifies all the selected factors into four groups namely, autonomous variables, dependent variables, linkage variables and driver variables. This research will help the supply chain architects to establish a better and reliable warehouse system. As this research involves analysis of multiple domains that is why a variety of users can refer to this work for their businesses, also the ISM approach gives a good accuracy of the hierarchy of the factors which helps in deciding the most effective chronology of the implementation of various warehousing operations. Researchers can also refer to this work to get insights of the significance of warehouse management in the supply chain and also the complete working of the ISM methodology.","PeriodicalId":32695,"journal":{"name":"Decision Making Applications in Management and Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48609711","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Shabnam Rahnamay Bonab, Gholamreza Haseli, Hamed Rajabzadeh, Saeid Jafarzadeh Ghoushchi, M. H. Keshteli, Hana Tomásková
Supplier selection process plays a vital role in supply chain management and is the most important variable in its success. With increasing environmental considerations, organizations must consider sustainability considerations and economic goals to protect the environment. Furthermore, the destructive effects of disruptions on the supply chain performance of companies have prompted organizational experts to pay special attention to the concept of resilience. This study developed an integrated approach based on the extended version of Multi-Criteria Decision-Making (MCDM) methods in a spherical fuzzy (SFS) environment to address sustainable and resilient IoT supplier selection. In the proposed approach, the main criteria (i.e., resilience, and sustainability) have been used in the supplier selection process. Then, these criteria are weighted using the developed SFS-Best-Worst Method (BWM), which reduces uncertainty in pairwise comparisons. In the next step, the 14 selected IoT suppliers are evaluated and prioritized by applying SFS-mulTi-noRmalization mUlti-Distance aSsessmenT (TRUST) that considers a multi-normalization algorithm to reduce subjectivity in normalized data. The results of this study shows that the pollution control and risk-taking sub-criteria are placed in the first and second priorities, respectively. The comparison of the results of the SFS-TRUST with other MCDM methods and sensitivity analysis demonstrates the performance of the proposed approach and its ranking stability in various scenarios.
{"title":"Sustainable resilient supplier selection for IoT implementation based on the integrated BWM and TRUST under spherical fuzzy sets","authors":"Shabnam Rahnamay Bonab, Gholamreza Haseli, Hamed Rajabzadeh, Saeid Jafarzadeh Ghoushchi, M. H. Keshteli, Hana Tomásková","doi":"10.31181/dmame12012023b","DOIUrl":"https://doi.org/10.31181/dmame12012023b","url":null,"abstract":"Supplier selection process plays a vital role in supply chain management and is the most important variable in its success. With increasing environmental considerations, organizations must consider sustainability considerations and economic goals to protect the environment. Furthermore, the destructive effects of disruptions on the supply chain performance of companies have prompted organizational experts to pay special attention to the concept of resilience. This study developed an integrated approach based on the extended version of Multi-Criteria Decision-Making (MCDM) methods in a spherical fuzzy (SFS) environment to address sustainable and resilient IoT supplier selection. In the proposed approach, the main criteria (i.e., resilience, and sustainability) have been used in the supplier selection process. Then, these criteria are weighted using the developed SFS-Best-Worst Method (BWM), which reduces uncertainty in pairwise comparisons. In the next step, the 14 selected IoT suppliers are evaluated and prioritized by applying SFS-mulTi-noRmalization mUlti-Distance aSsessmenT (TRUST) that considers a multi-normalization algorithm to reduce subjectivity in normalized data. The results of this study shows that the pollution control and risk-taking sub-criteria are placed in the first and second priorities, respectively. The comparison of the results of the SFS-TRUST with other MCDM methods and sensitivity analysis demonstrates the performance of the proposed approach and its ranking stability in various scenarios.","PeriodicalId":32695,"journal":{"name":"Decision Making Applications in Management and Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42696293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-15DOI: 10.31181/dmame0306102022c
Rishikesh Chaurasiya, D. Jain
Here in this article, a hybrid MCDM method on the Pythagorean fuzzy-environment is presented. This method is based on the Pythagorean Fuzzy Method based on Removal Effects of Criterion (PF-MEREC) and Stepwise Weight Assessment Ratio Analysis (SWARA) approaches. Here, the objective and subjective weights are assessed by PF-MEREC, SWARA model and the preference order ranking of the various alternatives is done through Complex Proportional Assessment (COPRAS) framework on the Pythagorean fuzzy set (PFS). The proposed method is the hybrid model of MEREC, SWARA and COPRAS methods. Further, the proposed model is used to identify the best banking management software (BMS) so that the bank can choose the robust bank management software tool to enhance its efficiency and excellence. Thereafter, a comparative discussion and sensitivity analysis of the proposed model is done with the existing techniques to judge the reasonability and efficiency of the proposed model.
{"title":"Hybrid MCDM method on pythagorean fuzzy set and its application","authors":"Rishikesh Chaurasiya, D. Jain","doi":"10.31181/dmame0306102022c","DOIUrl":"https://doi.org/10.31181/dmame0306102022c","url":null,"abstract":"Here in this article, a hybrid MCDM method on the Pythagorean fuzzy-environment is presented. This method is based on the Pythagorean Fuzzy Method based on Removal Effects of Criterion (PF-MEREC) and Stepwise Weight Assessment Ratio Analysis (SWARA) approaches. Here, the objective and subjective weights are assessed by PF-MEREC, SWARA model and the preference order ranking of the various alternatives is done through Complex Proportional Assessment (COPRAS) framework on the Pythagorean fuzzy set (PFS). The proposed method is the hybrid model of MEREC, SWARA and COPRAS methods. Further, the proposed model is used to identify the best banking management software (BMS) so that the bank can choose the robust bank management software tool to enhance its efficiency and excellence. Thereafter, a comparative discussion and sensitivity analysis of the proposed model is done with the existing techniques to judge the reasonability and efficiency of the proposed model.","PeriodicalId":32695,"journal":{"name":"Decision Making Applications in Management and Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44218554","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-15DOI: 10.31181/dmame060128022023b
Misty Blessley, Randy Davila, T. Hale, R. Pepper
The burning number of a graph models the rate at which a disease, information, or other externality can propagate across a network. The burning number is known to be NP-hard even for a tree. Herein, we define a relative of the burning number that we coin the contagion number (CN). We aver that the CN is a better metric to model disease spread than the burning number as it only counts first time infections (i.e., constrains a node from getting the same disease/same variant/same alarm more than once). This is important because the Centers for Disease Control and Prevention report that COVID-19 reinfections are rare. This paper delineates a method to solve for the contagion number of any tree, in polynomial time, which addresses how fast a disease could spread (i.e., a worst-cast analysis) and then employs simulation to determine the average contagion number (ACN) (i.e., a most-likely analysis) of how fast a disease would spread. The latter is analyzed on scale-free graphs, which are used to model human social networks generated through a preferential attachment mechanism. With CN differing across network structures and almost identical to ACN, our findings advance disease spread understanding and reveal the importance of network structure. In a borderless world without replete resources, understanding disease spread can do much to inform public policy and managerial decision makers’ allocation decisions. Furthermore, our direct interactions with supply chain executives at two COVID-19 vaccine developers provided practical grounding on what the results suggest for achieving social welfare objectives.
{"title":"The contagion number: How fast can a disease spread?","authors":"Misty Blessley, Randy Davila, T. Hale, R. Pepper","doi":"10.31181/dmame060128022023b","DOIUrl":"https://doi.org/10.31181/dmame060128022023b","url":null,"abstract":"The burning number of a graph models the rate at which a disease, information, or other externality can propagate across a network. The burning number is known to be NP-hard even for a tree. Herein, we define a relative of the burning number that we coin the contagion number (CN). We aver that the CN is a better metric to model disease spread than the burning number as it only counts first time infections (i.e., constrains a node from getting the same disease/same variant/same alarm more than once). This is important because the Centers for Disease Control and Prevention report that COVID-19 reinfections are rare. This paper delineates a method to solve for the contagion number of any tree, in polynomial time, which addresses how fast a disease could spread (i.e., a worst-cast analysis) and then employs simulation to determine the average contagion number (ACN) (i.e., a most-likely analysis) of how fast a disease would spread. The latter is analyzed on scale-free graphs, which are used to model human social networks generated through a preferential attachment mechanism. With CN differing across network structures and almost identical to ACN, our findings advance disease spread understanding and reveal the importance of network structure. In a borderless world without replete resources, understanding disease spread can do much to inform public policy and managerial decision makers’ allocation decisions. Furthermore, our direct interactions with supply chain executives at two COVID-19 vaccine developers provided practical grounding on what the results suggest for achieving social welfare objectives.","PeriodicalId":32695,"journal":{"name":"Decision Making Applications in Management and Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48900504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The terms of competitiveness at the level of places and sustainable development were created in the 1980s and 1990s. In the beginning, most researchers emphasized the dimension of economic competitiveness, but in recent decades, other aspects of competitiveness, such as socio-cultural and environmental, have been highlighted. The aim of the present research is evaluation the social-cultural competitiveness in the city of Kermanshah based on a sustainable development approach. This research is descriptive and analytical, the TOPSIS model was used for data analysis, and Entropy was used to weight the indicators. After applying the weight of the indicators in the TOPSIS model, The research findings showed that the city of Kermanshah in the TOPSIS model, ranks 15th with a coefficient of 0.209; in the MABAC model, ranks 14th with a coefficient of -0.116 and in the EDAS model, ranks 14th with a coefficient of 0.122579271 is in the last and 14th position of socio-cultural competitiveness. The results showed that; Considering the nature of urban competitiveness, which is multidimensional, it is necessary to avoid a one-sided approach in urban competitiveness planning and to consider the socio-cultural, environmental, and security dimensions of urban competitiveness in an integrated manner. To improve the competitiveness of Iranian cities, while paying attention to the internal competitive advantages of the 15 studied cities, special attention should be paid to the fields of economic, environmental, socio-cultural, and security competitiveness. Each of these cities concerns their competitive role in transnational dimensions. This requires special attention to the national macro-plans.
{"title":"Evaluation of the social-cultural competitiveness of cities based on sustainable development approach","authors":"H. Komasi, S. Zolfani, Ali Nemati","doi":"10.31181/dmame06012023k","DOIUrl":"https://doi.org/10.31181/dmame06012023k","url":null,"abstract":"The terms of competitiveness at the level of places and sustainable development were created in the 1980s and 1990s. In the beginning, most researchers emphasized the dimension of economic competitiveness, but in recent decades, other aspects of competitiveness, such as socio-cultural and environmental, have been highlighted. The aim of the present research is evaluation the social-cultural competitiveness in the city of Kermanshah based on a sustainable development approach. This research is descriptive and analytical, the TOPSIS model was used for data analysis, and Entropy was used to weight the indicators. After applying the weight of the indicators in the TOPSIS model, The research findings showed that the city of Kermanshah in the TOPSIS model, ranks 15th with a coefficient of 0.209; in the MABAC model, ranks 14th with a coefficient of -0.116 and in the EDAS model, ranks 14th with a coefficient of 0.122579271 is in the last and 14th position of socio-cultural competitiveness. The results showed that; Considering the nature of urban competitiveness, which is multidimensional, it is necessary to avoid a one-sided approach in urban competitiveness planning and to consider the socio-cultural, environmental, and security dimensions of urban competitiveness in an integrated manner. To improve the competitiveness of Iranian cities, while paying attention to the internal competitive advantages of the 15 studied cities, special attention should be paid to the fields of economic, environmental, socio-cultural, and security competitiveness. Each of these cities concerns their competitive role in transnational dimensions. This requires special attention to the national macro-plans.","PeriodicalId":32695,"journal":{"name":"Decision Making Applications in Management and Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49489437","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The suggested hybridized framework offers a paradigm for performance optimization-reliability-based analysis of milk processing unit’s (MPU) failure behavior in the dairy industry. The proposed hybridized framework led to the development of fuzzy Jaya Based Lambda-Tau (JBLT) technique-based mathematical model for computing various performance parameters of the under-consideration unit. The availability of the system drops by 0.044% as the level of uncertainty or spread level increases from ± 15% to ± 25% and drops to 0.088% as the level of uncertainty increases from ± 25% to ± 60%. To corroborate the system’s availability downward trend, the results of JBLT approach were compared with Particle Swarm Optimization-Based Lambda-Tau (PSOBLT) and conventional Fuzzy Lambda-Tau (FLT) techniques. The analysis findings were given to the maintenance manager so they could create the best maintenance schedule for the considered plant.
{"title":"Reliability based framework for failure analysis in milk process industry","authors":"Nand Gopal, Dilbagh Panchal","doi":"10.31181/dmame24022023g","DOIUrl":"https://doi.org/10.31181/dmame24022023g","url":null,"abstract":"The suggested hybridized framework offers a paradigm for performance optimization-reliability-based analysis of milk processing unit’s (MPU) failure behavior in the dairy industry. The proposed hybridized framework led to the development of fuzzy Jaya Based Lambda-Tau (JBLT) technique-based mathematical model for computing various performance parameters of the under-consideration unit. The availability of the system drops by 0.044% as the level of uncertainty or spread level increases from ± 15% to ± 25% and drops to 0.088% as the level of uncertainty increases from ± 25% to ± 60%. To corroborate the system’s availability downward trend, the results of JBLT approach were compared with Particle Swarm Optimization-Based Lambda-Tau (PSOBLT) and conventional Fuzzy Lambda-Tau (FLT) techniques. The analysis findings were given to the maintenance manager so they could create the best maintenance schedule for the considered plant.","PeriodicalId":32695,"journal":{"name":"Decision Making Applications in Management and Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48472019","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The acceptance sampling plan (ASP) is one of the key statistics resources in the industrial sector. It entails the decision-making process for accepting or rejecting the products. The investigated quality parameter is the test unit's mean lifespan. This study develops a new ASP for Zeghdοudi distribution (ZD) when the lifetime is shortened to a specific degree. The optimal plan parameters are accomplished by obtaining the minimum sample size mandatory to ensure the identified mean lifetime for fixing the consumer's risk. Besides, the characteristic operating function (OCF) values for the ASP are displayed, and the producer's risk is determined. Several helpful tables are developed for the suggested ASP based on the ZD for suitable employment. An actual data set is fitted to the Zeghdoudi model and other models to examine the applicability of the suggested ASP in the production sector.
{"title":"Zeghdοudi distribution in acceptance sampling plans based on truncated life tests with real data application","authors":"Rehab Alsultan, A. Al-Omari","doi":"10.31181/dmame05012023a","DOIUrl":"https://doi.org/10.31181/dmame05012023a","url":null,"abstract":"The acceptance sampling plan (ASP) is one of the key statistics resources in the industrial sector. It entails the decision-making process for accepting or rejecting the products. The investigated quality parameter is the test unit's mean lifespan. This study develops a new ASP for Zeghdοudi distribution (ZD) when the lifetime is shortened to a specific degree. The optimal plan parameters are accomplished by obtaining the minimum sample size mandatory to ensure the identified mean lifetime for fixing the consumer's risk. Besides, the characteristic operating function (OCF) values for the ASP are displayed, and the producer's risk is determined. Several helpful tables are developed for the suggested ASP based on the ZD for suitable employment. An actual data set is fitted to the Zeghdoudi model and other models to examine the applicability of the suggested ASP in the production sector.","PeriodicalId":32695,"journal":{"name":"Decision Making Applications in Management and Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41918470","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The Travelling Salesman Problem (TSP) is a well-known combinatorial optimization problem that belongs to a class of problems known as NP-hard, which is an exceptional case of travelling salesman problem (TSP), which determines a set of routes enabling multiple salesmen to start at and return to home cities (depots). The penguins search optimization algorithm (PeSOA) is a new metaheuristic optimization algorithm. In this paper, we present a discrete penguins search optimization algorithm (PeSOA) for solving the multiple travelling salesman problem (MTSP). The PeSOA evaluated by a set of benchmarks of TSP instance from TSPLIB library. The experimental results show that PeSOA is very efficient in finding the right solutions in a reasonable time
{"title":"Efficient routing optimization with discrete penguins search algorithm for MTSP","authors":"","doi":"10.31181/dmame04092023m","DOIUrl":"https://doi.org/10.31181/dmame04092023m","url":null,"abstract":"The Travelling Salesman Problem (TSP) is a well-known combinatorial optimization problem that belongs to a class of problems known as NP-hard, which is an exceptional case of travelling salesman problem (TSP), which determines a set of routes enabling multiple salesmen to start at and return to home cities (depots). The penguins search optimization algorithm (PeSOA) is a new metaheuristic optimization algorithm. In this paper, we present a discrete penguins search optimization algorithm (PeSOA) for solving the multiple travelling salesman problem (MTSP). The PeSOA evaluated by a set of benchmarks of TSP instance from TSPLIB library. The experimental results show that PeSOA is very efficient in finding the right solutions in a reasonable time","PeriodicalId":32695,"journal":{"name":"Decision Making Applications in Management and Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41725479","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-15DOI: 10.31181/dmame181221015k
Md Faysal Kabir, Sahadev Roy
: In this article, the hazard-based accident duration model and the reaction time due to various types of distractions are considered. This analysis is mainly considered T-junction or T-junctions like all other forms of road geometries which are more prone to accident. The model proposed is constructed by using a electronics devices along with driving simulator, to study the behavior of the yang inexperienced drivers as well as an experienced driver about their reaction by calling their phone from unknown numbers intentionally. The results show that drivers distracted by mobile phones uses the hard breaking due to least available time to respond after identification of an event. Some of the research and theory bearing on decision making and risk perception, driver situation awareness, and possible mediators of risk-taking is also analyzed here.
{"title":"Hazard perception test among young inexperienced drivers and risk analysis while driving through a T-junction","authors":"Md Faysal Kabir, Sahadev Roy","doi":"10.31181/dmame181221015k","DOIUrl":"https://doi.org/10.31181/dmame181221015k","url":null,"abstract":": In this article, the hazard-based accident duration model and the reaction time due to various types of distractions are considered. This analysis is mainly considered T-junction or T-junctions like all other forms of road geometries which are more prone to accident. The model proposed is constructed by using a electronics devices along with driving simulator, to study the behavior of the yang inexperienced drivers as well as an experienced driver about their reaction by calling their phone from unknown numbers intentionally. The results show that drivers distracted by mobile phones uses the hard breaking due to least available time to respond after identification of an event. Some of the research and theory bearing on decision making and risk perception, driver situation awareness, and possible mediators of risk-taking is also analyzed here.","PeriodicalId":32695,"journal":{"name":"Decision Making Applications in Management and Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45086455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-15DOI: 10.31181/dmame0317102022r
Vishnu Kumar Rai, Santonab Chakraborty, S. Chakraborty
COVID-19 is a raging pandemic that has created havoc with its impact ranging from loss of millions of human lives to social and economic disruptions of the entire world. The catastrophic shock of COVID-19 in India is also enormous. Currently, India has the largest number of COVID cases in Asia. Therefore, error-free prediction, quick diagnosis, disease identification, isolation and treatment of a COVID patient have become extremely important. Nowadays, mining knowledge and providing scientific decision making for diagnosis of diseases from clinical datasets has found wide-ranging applications in healthcare sector. In this direction, among different data mining tools, association rule mining has already emerged out as a popular technique to extract invaluable information and develop important knowledge-base to help in intelligent diagnosis of distinct diseases quickly and automatically. In this paper, an attempt is put forward to develop a predictive model based on frequent pattern growth algorithm of association rule mining to determine the likelihood of COVID-19 in a patient. It identifies breathing problem, fever, dry cough, sore throat, abroad travel and attended large gathering as the main indicators of COVID-19. Based on a large clinical dataset, a linear regression model is also proposed having an accuracy of 73.9% in correctly predicting the occurrence of COVID-19.
{"title":"Association rule mining for prediction of COVID-19","authors":"Vishnu Kumar Rai, Santonab Chakraborty, S. Chakraborty","doi":"10.31181/dmame0317102022r","DOIUrl":"https://doi.org/10.31181/dmame0317102022r","url":null,"abstract":"COVID-19 is a raging pandemic that has created havoc with its impact ranging from loss of millions of human lives to social and economic disruptions of the entire world. The catastrophic shock of COVID-19 in India is also enormous. Currently, India has the largest number of COVID cases in Asia. Therefore, error-free prediction, quick diagnosis, disease identification, isolation and treatment of a COVID patient have become extremely important. Nowadays, mining knowledge and providing scientific decision making for diagnosis of diseases from clinical datasets has found wide-ranging applications in healthcare sector. In this direction, among different data mining tools, association rule mining has already emerged out as a popular technique to extract invaluable information and develop important knowledge-base to help in intelligent diagnosis of distinct diseases quickly and automatically. In this paper, an attempt is put forward to develop a predictive model based on frequent pattern growth algorithm of association rule mining to determine the likelihood of COVID-19 in a patient. It identifies breathing problem, fever, dry cough, sore throat, abroad travel and attended large gathering as the main indicators of COVID-19. Based on a large clinical dataset, a linear regression model is also proposed having an accuracy of 73.9% in correctly predicting the occurrence of COVID-19.","PeriodicalId":32695,"journal":{"name":"Decision Making Applications in Management and Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47716654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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