This review research paper provides a comprehensive analysis of the advancements, challenges, and methodologies in autonomous navigation and obstacle avoidance for smart robotic wheelchairs. The integration of robotics and assistive technology has revolutionized mobility solutions for individuals with impairments, enabling them to navigate complex environments independently. The paper examines the various sensor modalities, machine learning algorithms, and computer vision techniques employed for environment perception and obstacle recognition. It discusses path planning algorithms, motion control strategies, and decision-making processes for autonomous navigation. The review also addresses limitations, such as localization accuracy and dynamic environment modelling, while highlighting recent research advancements and suggesting future directions. Overall, this paper serves as a valuable resource for researchers and practitioners in the field of smart robotic wheelchairs, aiming to enhance mobility and quality of life for individuals with mobility impairments.
{"title":"Autonomous navigation and obstacle avoidance in smart robotic wheelchairs","authors":"S. K. Sahoo, Bibhuti Bhusan Choudhury","doi":"10.31181/jdaic10019022024s","DOIUrl":"https://doi.org/10.31181/jdaic10019022024s","url":null,"abstract":"This review research paper provides a comprehensive analysis of the advancements, challenges, and methodologies in autonomous navigation and obstacle avoidance for smart robotic wheelchairs. The integration of robotics and assistive technology has revolutionized mobility solutions for individuals with impairments, enabling them to navigate complex environments independently. The paper examines the various sensor modalities, machine learning algorithms, and computer vision techniques employed for environment perception and obstacle recognition. It discusses path planning algorithms, motion control strategies, and decision-making processes for autonomous navigation. The review also addresses limitations, such as localization accuracy and dynamic environment modelling, while highlighting recent research advancements and suggesting future directions. Overall, this paper serves as a valuable resource for researchers and practitioners in the field of smart robotic wheelchairs, aiming to enhance mobility and quality of life for individuals with mobility impairments.","PeriodicalId":118691,"journal":{"name":"Journal of Decision Analytics and Intelligent Computing","volume":"10 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139959109","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 paper addresses the selection of the most favorable alternative in the form of assault rifles to meet the requirements arising from modern combat operations. The complexity of the problem, conditioned by the different structural elements of automatic rifles and the specific situations of their use, has caused the application of Multi-Criteria Decision-making (MCDM) methods. A hybrid model was developed to guide the selection of the appropriate automatic rifle. The criteria were defined by experts, where the calculation of the weight coefficients of criteria was performed using the LMAW method Employing the grey EDAS method for MCDM, the study identifies an assault rifle that offers the most advantageous capabilities for carrying out firing tasks in the context of daily combat operations, with the aim of equipping the armed forces and raising the operational capability of the units. The validity of this model was verified through sensitivity analysis involving the adjustment of criteria weight coefficients.
{"title":"Application of the new hybrid model LMAW-G-EDAS multi-criteria decision-making when choosing an assault rifle for the needs of the army","authors":"Marko Radovanović, A. Petrovski, Elif Cirkin, Aner Behlić, Željko Jokić, Denis Chemezov, E. Hashimov, Mouhamed Bayane Bouraima, Chiranjibe Jana","doi":"10.31181/jdaic10021012024r","DOIUrl":"https://doi.org/10.31181/jdaic10021012024r","url":null,"abstract":"The paper addresses the selection of the most favorable alternative in the form of assault rifles to meet the requirements arising from modern combat operations. The complexity of the problem, conditioned by the different structural elements of automatic rifles and the specific situations of their use, has caused the application of Multi-Criteria Decision-making (MCDM) methods. A hybrid model was developed to guide the selection of the appropriate automatic rifle. The criteria were defined by experts, where the calculation of the weight coefficients of criteria was performed using the LMAW method Employing the grey EDAS method for MCDM, the study identifies an assault rifle that offers the most advantageous capabilities for carrying out firing tasks in the context of daily combat operations, with the aim of equipping the armed forces and raising the operational capability of the units. The validity of this model was verified through sensitivity analysis involving the adjustment of criteria weight coefficients.","PeriodicalId":118691,"journal":{"name":"Journal of Decision Analytics and Intelligent Computing","volume":"15 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139523417","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}
In recent times, Indian Stock Market (ISM) has been witnessing a surge in the number of IPOs listed in stock exchanges. However, in many occasions it has been noticed that post-listing performance of several IPOs are below par to the expectations of the investors. IPO performance has been one of the major concerns. In this context, the present paper endeavours to carry out a comparative performance assessment of a list of IPOs. We consider a period of three years after listing. Our sample consists of a list of IPOs having heterogeneous nature of business operations and introduced in 2018. We consider two aspects of the performance such as market-based indicators and fundamental efficiency in terms of profitability, liquidity and risk. For comparison, LOgarithmic Percentage Change-driven Objective Weighting (LOPCOW) is used. The study period is considered as Fy 2020-21. The results reflect that for IPOs, market performance does not necessarily because of the fundamental efficiency. Further, we notice that the nature of equity ownership does not influence the market performance significantly. We surmise that during initial years, the performance of the IPOs at the marketplace is more driven by speculations and short-term goals of the investors. The result of validation test indicates that the ranking using LOPCOW method is comparable and consistent with a widely used model like Entropy.
{"title":"A Performance based Ranking of Initial Public Offerings (IPOs) in India","authors":"S. Biswas, Neha Joshi","doi":"10.31181/10023022023b","DOIUrl":"https://doi.org/10.31181/10023022023b","url":null,"abstract":"In recent times, Indian Stock Market (ISM) has been witnessing a surge in the number of IPOs listed in stock exchanges. However, in many occasions it has been noticed that post-listing performance of several IPOs are below par to the expectations of the investors. IPO performance has been one of the major concerns. In this context, the present paper endeavours to carry out a comparative performance assessment of a list of IPOs. We consider a period of three years after listing. Our sample consists of a list of IPOs having heterogeneous nature of business operations and introduced in 2018. We consider two aspects of the performance such as market-based indicators and fundamental efficiency in terms of profitability, liquidity and risk. For comparison, LOgarithmic Percentage Change-driven Objective Weighting (LOPCOW) is used. The study period is considered as Fy 2020-21. The results reflect that for IPOs, market performance does not necessarily because of the fundamental efficiency. Further, we notice that the nature of equity ownership does not influence the market performance significantly. We surmise that during initial years, the performance of the IPOs at the marketplace is more driven by speculations and short-term goals of the investors. The result of validation test indicates that the ranking using LOPCOW method is comparable and consistent with a widely used model like Entropy.","PeriodicalId":118691,"journal":{"name":"Journal of Decision Analytics and Intelligent Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129915468","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}
Using a dummy variable, we evaluate commodities in addition to macroeconomic considerations of the Indian securities market from 2010 to 2021, which includes the era of the Covid 19 crises. We used the Bombay Stock Exchange (BSE) (Sensex) for securities market performance and developed a Vector Auto regressive models that combines the short- and long-run model of economics. On stock price indexes, we discovered that the Indian securities market reflects both macroeconomic indicators and prices of commodity. Growth in the economy, inflation, interest, rates, currency rates, crude oil prices, and gold prices are all factors to consider were all used in this study to see how they affected BSE (Sensex) prices during the Covid 19 crises. In their first difference, all series were judged to be stationary. We discovered that shocks to all eight factors had both positive and negative effects on BSE (Sensex) prices in the short and long term, including Covid 19 crises. Each securities market index’s most significant impulse is its own shock, decreasing from short to long-term. We also used the Joint Co-Integration Test to detect and confirm the lack of a long-term equilibrium link (cointegration) between all eight variables, resulting in four cointegration equations with an estimated error correction term at the 0.05 level (speed of adjustment towards equilibrium) of 0.007362. Vector Error Correction Mode (VECM), on the other hand, suggests that the BSE (Sensex) has a significant value with its lagged values of.007362 and 0.517952. We created Vector Auto regressive (VAR) models for the BSE (Sensex) using eight independent variables, including Dummy variables, but their statistics were not significant, despite the fact that the lagged value of crude oil, gold prices, the rupee, and the BSE (Sensex) lagged value were all significant. We proceed to estimate VECM. We proved the short and long-term effects of lagged BSE(Sensex) prices, crude oil prices, gold prices, and the currency on the BSE (SENSEX) using several robustness tests. Dummy factors have also been included to see how the Covid 19 crisis affected the BSE (Sensex) prices. We discovered that crude oil prices followed value, gold prices lagged value, and rupees based on the dollar had a significant impact on BSE(Sensex) pricing over the study period, including the Covid 19 crises from March 2020 to June 2021.
{"title":"VAR and VECM models were used to investigate the factors that influence of Indian securities market performance, including the period of Covid 19's financial crises","authors":"Lotica Surana","doi":"10.31181/10025112023s","DOIUrl":"https://doi.org/10.31181/10025112023s","url":null,"abstract":"Using a dummy variable, we evaluate commodities in addition to macroeconomic considerations of the Indian securities market from 2010 to 2021, which includes the era of the Covid 19 crises. We used the Bombay Stock Exchange (BSE) (Sensex) for securities market performance and developed a Vector Auto regressive models that combines the short- and long-run model of economics. On stock price indexes, we discovered that the Indian securities market reflects both macroeconomic indicators and prices of commodity. Growth in the economy, inflation, interest, rates, currency rates, crude oil prices, and gold prices are all factors to consider were all used in this study to see how they affected BSE (Sensex) prices during the Covid 19 crises. In their first difference, all series were judged to be stationary. We discovered that shocks to all eight factors had both positive and negative effects on BSE (Sensex) prices in the short and long term, including Covid 19 crises. Each securities market index’s most significant impulse is its own shock, decreasing from short to long-term. We also used the Joint Co-Integration Test to detect and confirm the lack of a long-term equilibrium link (cointegration) between all eight variables, resulting in four cointegration equations with an estimated error correction term at the 0.05 level (speed of adjustment towards equilibrium) of 0.007362. Vector Error Correction Mode (VECM), on the other hand, suggests that the BSE (Sensex) has a significant value with its lagged values of.007362 and 0.517952. We created Vector Auto regressive (VAR) models for the BSE (Sensex) using eight independent variables, including Dummy variables, but their statistics were not significant, despite the fact that the lagged value of crude oil, gold prices, the rupee, and the BSE (Sensex) lagged value were all significant. We proceed to estimate VECM. We proved the short and long-term effects of lagged BSE(Sensex) prices, crude oil prices, gold prices, and the currency on the BSE (SENSEX) using several robustness tests. Dummy factors have also been included to see how the Covid 19 crisis affected the BSE (Sensex) prices. We discovered that crude oil prices followed value, gold prices lagged value, and rupees based on the dollar had a significant impact on BSE(Sensex) pricing over the study period, including the Covid 19 crises from March 2020 to June 2021.","PeriodicalId":118691,"journal":{"name":"Journal of Decision Analytics and Intelligent Computing","volume":"38 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139236307","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 fixed charge transportation problem is a nonlinear programming problem in which a fixed charge is incurred if a distribution variable assumes a nonzero value. Its structure is almost identical to that of a linear programming problem, and indeed it can be written as a mixed-integer linear program. In this paper, we consider the fixed charge transportation problem under uncertainty, particularly when the direct and fixed costs are the generalized trapezoidal fuzzy numbers. The first step it transforms into the classical fuzzy transportation problem. The next we obtain the best approximation fuzzy on the optimal value of the fuzzy fixed-charge transportation problem. This method obtains a lower and upper bound both on the fuzzy optimal value of the fuzzy fixed-charge transportation problem which can be easily obtained by using the approximation solution. Conclusion: we propose a new method as the best approximation method, with representation both of the transportation cost and the fixed cost, to find a fuzzy approximation solution close to the optimal solution for fuzzy fixed charge transportation problem.
{"title":"A heuristic approach for fuzzy fixed charge transportation problem","authors":"Ali Mahmoodirad, S. Niroomand","doi":"10.31181/jdaic10005092023m","DOIUrl":"https://doi.org/10.31181/jdaic10005092023m","url":null,"abstract":"The fixed charge transportation problem is a nonlinear programming problem in which a fixed charge is incurred if a distribution variable assumes a nonzero value. Its structure is almost identical to that of a linear programming problem, and indeed it can be written as a mixed-integer linear program. In this paper, we consider the fixed charge transportation problem under uncertainty, particularly when the direct and fixed costs are the generalized trapezoidal fuzzy numbers. The first step it transforms into the classical fuzzy transportation problem. The next we obtain the best approximation fuzzy on the optimal value of the fuzzy fixed-charge transportation problem. This method obtains a lower and upper bound both on the fuzzy optimal value of the fuzzy fixed-charge transportation problem which can be easily obtained by using the approximation solution. Conclusion: we propose a new method as the best approximation method, with representation both of the transportation cost and the fixed cost, to find a fuzzy approximation solution close to the optimal solution for fuzzy fixed charge transportation problem.","PeriodicalId":118691,"journal":{"name":"Journal of Decision Analytics and Intelligent Computing","volume":"1991 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125518161","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}
Humanitarian relief transportation and mass fatality management activities are the most strenuous tasks after a natural or artificial disaster. A feasible and realistic transport model is essential for accomplishing the tasks in a planned way. Covering Salesman Problem (CSP) is a variant of Traveling Salesman Problem (TSP) which has been used in many application areas, including disaster management. In this paper, we consider a bi-objective CSP in an uncertain environment where Interval Type 2 fuzzy numbers represent the costs of the edges. A new local search technique is introduced in the memetic algorithm, which has been used to solve the problem. A computational experiment on a set of instances indicates the effectiveness of the introduced local search technique along with the proposed methodology.
{"title":"Bi-objective covering salesman problem with uncertainty","authors":"S. Tripathy","doi":"10.31181/jdaic10015082023t","DOIUrl":"https://doi.org/10.31181/jdaic10015082023t","url":null,"abstract":"Humanitarian relief transportation and mass fatality management activities are the most strenuous tasks after a natural or artificial disaster. A feasible and realistic transport model is essential for accomplishing the tasks in a planned way. Covering Salesman Problem (CSP) is a variant of Traveling Salesman Problem (TSP) which has been used in many application areas, including disaster management. In this paper, we consider a bi-objective CSP in an uncertain environment where Interval Type 2 fuzzy numbers represent the costs of the edges. A new local search technique is introduced in the memetic algorithm, which has been used to solve the problem. A computational experiment on a set of instances indicates the effectiveness of the introduced local search technique along with the proposed methodology.","PeriodicalId":118691,"journal":{"name":"Journal of Decision Analytics and Intelligent Computing","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127698267","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}
Sensors play an important role in monitoring, detecting, recording and recording the physical and environmental conditions of a particular place. These physical conditions mainly include temperature, sound, wind, etc. These nodes are connected to each other via a transmission channel and the nodes are battery-operated. So, energy efficient algorithms are needed to reduce energy consumption in the overall setup and increase the lifetime of sensor nodes. In this paper, we propose a method to solve the problem of routing in “Wireless Sensor Networks”, forming clusters such that there are minimal node transfers and the overall energy consumption of the system is reduced. We have implemented Multiple Objective Particle Swarm Optimization (MOPSO) algorithm to devise a technique that considers several parameters like temperature, minimal clustering, routing path distance and energy efficiency to obtain optimal clusters.
{"title":"A method of finding optimal number of clusters in a wireless network based on power efficiency using MOPSO","authors":"Harinandan Tunga, Debasis Giri","doi":"10.31181/jdaic10005082023t","DOIUrl":"https://doi.org/10.31181/jdaic10005082023t","url":null,"abstract":"Sensors play an important role in monitoring, detecting, recording and recording the physical and environmental conditions of a particular place. These physical conditions mainly include temperature, sound, wind, etc. These nodes are connected to each other via a transmission channel and the nodes are battery-operated. So, energy efficient algorithms are needed to reduce energy consumption in the overall setup and increase the lifetime of sensor nodes. In this paper, we propose a method to solve the problem of routing in “Wireless Sensor Networks”, forming clusters such that there are minimal node transfers and the overall energy consumption of the system is reduced. We have implemented Multiple Objective Particle Swarm Optimization (MOPSO) algorithm to devise a technique that considers several parameters like temperature, minimal clustering, routing path distance and energy efficiency to obtain optimal clusters.","PeriodicalId":118691,"journal":{"name":"Journal of Decision Analytics and Intelligent Computing","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126196158","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 conception of the bipolar complex fuzzy set (BCFS) is one of the fundamental and significant modifications of the fuzzy set (FS) to tackle the tricky and awkward information. BCFS has a rich and wider structure and has been utilized in various fields. In this article, we introduce the concept of bipolar complex fuzzy (BCF) subalgebras (BCFSAs), BCF ideals (BCFIs) of a BCK/BCI-algebra along with certain properties. Further, we investigate the relations between BCFSA and a BCFI and a necessary condition for BCFSA to be a BCFI. We also investigate characterizations of BCFI. Moreover, we introduce the notion of equivalence relations on the collection of all BCFIs of BCK/BCI algebra and the associated properties of equivalence relations.
{"title":"Bipolar complex fuzzy subalgebras and ideals of BCK/BCI-algebras","authors":"Tahir Mahmood, U. Rehman","doi":"10.31181/jdaic10021042023m","DOIUrl":"https://doi.org/10.31181/jdaic10021042023m","url":null,"abstract":"The conception of the bipolar complex fuzzy set (BCFS) is one of the fundamental and significant modifications of the fuzzy set (FS) to tackle the tricky and awkward information. BCFS has a rich and wider structure and has been utilized in various fields. In this article, we introduce the concept of bipolar complex fuzzy (BCF) subalgebras (BCFSAs), BCF ideals (BCFIs) of a BCK/BCI-algebra along with certain properties. Further, we investigate the relations between BCFSA and a BCFI and a necessary condition for BCFSA to be a BCFI. We also investigate characterizations of BCFI. Moreover, we introduce the notion of equivalence relations on the collection of all BCFIs of BCK/BCI algebra and the associated properties of equivalence relations.","PeriodicalId":118691,"journal":{"name":"Journal of Decision Analytics and Intelligent Computing","volume":"111 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124068060","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}
Human qualitative judgments are often characterized by uncertainty and predictability. Decision-makers tend to be more confident in making linguistic decisions than in crisp value judgments. MEREC is capable of achieving relative objective weights of several conflicting criteria. This paper contains two parts, first, the extension of MEREC method in fuzzy circumstances based on linguistic terms in which a parabolic measure has been used to calculate the overall performance of alternatives as it is able to work according the definition of TFNs and to show the applicability, a simple decision matrix is analysed in a fuzzy environment. Second, a new hybrid ranking methodology Fuzzy MEREC-TOPSIS for multi criteria decision making. Further, to illustrate the credibility and effectiveness of the proposed hybrid ranking method, a real-world example of stock selection has been used. The portfolio is constructed using ranking of the stocks received through the proposed method and capital is allocated according to the order of preference of stocks. To validate the proposed ranking model, the next 30 days closing price of each stock is predicted by a deep recurrent neural network and the portfolio for future investments is analysed. The results of the future analysis validate the credibility of the portfolio.
{"title":"A fuzzy extension of MEREC method using parabolic measure and its applications","authors":"Monika Narang, Arun Kumar, Rajat Dhawan","doi":"10.31181/jdaic10020042023n","DOIUrl":"https://doi.org/10.31181/jdaic10020042023n","url":null,"abstract":"Human qualitative judgments are often characterized by uncertainty and predictability. Decision-makers tend to be more confident in making linguistic decisions than in crisp value judgments. MEREC is capable of achieving relative objective weights of several conflicting criteria. This paper contains two parts, first, the extension of MEREC method in fuzzy circumstances based on linguistic terms in which a parabolic measure has been used to calculate the overall performance of alternatives as it is able to work according the definition of TFNs and to show the applicability, a simple decision matrix is analysed in a fuzzy environment. Second, a new hybrid ranking methodology Fuzzy MEREC-TOPSIS for multi criteria decision making. Further, to illustrate the credibility and effectiveness of the proposed hybrid ranking method, a real-world example of stock selection has been used. The portfolio is constructed using ranking of the stocks received through the proposed method and capital is allocated according to the order of preference of stocks. To validate the proposed ranking model, the next 30 days closing price of each stock is predicted by a deep recurrent neural network and the portfolio for future investments is analysed. The results of the future analysis validate the credibility of the portfolio.","PeriodicalId":118691,"journal":{"name":"Journal of Decision Analytics and Intelligent Computing","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116004797","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 research aims to identify critical success factors for sustainable supply chain management (SSCM) systems of food and beverages (F&B) SMEs. Firstly the critical success factors were identified using a systematic literature review, further Structured Equation modeling has been done to analyze whether SSCM. The realistic insights presented in this study have the opportunity to further improve knowledge of the implementation of SSCM practices not only within the boundary of the industry but also to expand them to their supply chains. The aim of this research is to analyze whether SSCM practices are implemented at all stages in F&B SME’s supply chain. The research leads to the supportable supply chain management information by identifying CSF and developing an SSCM model for the sustainable growth of the firm. The research also provides useful insights into the fields that have been explored by existing literature.
{"title":"Sustainable Supply chain Systems of Food and Beverages SMEs: Analyzing sustainable performance using Structured Equation Modeling","authors":"V. Verma, Priyanka Bisht, Sudhanshu Joshi","doi":"10.31181/jdaic10016062022v","DOIUrl":"https://doi.org/10.31181/jdaic10016062022v","url":null,"abstract":"The research aims to identify critical success factors for sustainable supply chain management (SSCM) systems of food and beverages (F&B) SMEs. Firstly the critical success factors were identified using a systematic literature review, further Structured Equation modeling has been done to analyze whether SSCM. The realistic insights presented in this study have the opportunity to further improve knowledge of the implementation of SSCM practices not only within the boundary of the industry but also to expand them to their supply chains. The aim of this research is to analyze whether SSCM practices are implemented at all stages in F&B SME’s supply chain. The research leads to the supportable supply chain management information by identifying CSF and developing an SSCM model for the sustainable growth of the firm. The research also provides useful insights into the fields that have been explored by existing literature.","PeriodicalId":118691,"journal":{"name":"Journal of Decision Analytics and Intelligent Computing","volume":"354 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125639271","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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