Filters








21,001 Hits in 6.4 sec

Multi-Objective Markov Decision Processes for Data-Driven Decision Support

Daniel J Lizotte, Eric B Laber
2016 Journal of machine learning research  
We present new methodology based on Multi-Objective Markov Decision Processes for developing sequential decision support systems from data.  ...  Our approach uses sequential decision-making data to provide support that is useful to many different decision-makers, each with different, potentially time-varying preference.  ...  Figure 7 shows the NDP learned for Phase Acknowledgments We acknowledge support from the Natural Sciences and Engineering Research Council of Canada.  ... 
pmid:28018133 pmcid:PMC5179144 fatcat:khhqga24wbg7vmnnhm5kwyluxa

A Review of Data-Driven Decision-Making Methods for Industry 4.0 Maintenance Applications

Alexandros Bousdekis, Katerina Lepenioti, Dimitris Apostolou, Gregoris Mentzas
2021 Electronics  
The current paper reviews the literature on data-driven decision-making in maintenance and outlines directions for future research towards data-driven decision-making for Industry 4.0 maintenance applications  ...  of the cloud continuum for optimal deployment of decision-making services; capability of decision-making methods to cope with big data; incorporation of advanced security mechanisms; and coupling decision-making  ...  However, there is the need for data-driven generic decision-making algorithms representing the decision-making process instead of the physical process.  ... 
doi:10.3390/electronics10070828 doaj:8accfa8ec357433dbb02cde449e3af6a fatcat:7q55ex2mezfstdllzfufryeo3a

Data Mining Based Marketing Decision Support System Using Hybrid Machine Learning Algorithm

Dr. T. Senthil Kumar
2020 Journal of Artificial Intelligence and Capsule Networks  
This research work proposed a data mining based decision support system using decision tree and artificial neural network as a hybrid approach to estimate the marketing strategies for an organization.  ...  Data mining based decision support system enhances the organization performance by analysing the ground reality.  ...  Based upon the applications, decision support system is categorized into  Data Driven Decision support system,  Communication driven decision support system,  Document driven decision support system  ... 
doi:10.36548//jaicn.2020.3.006 fatcat:y4sueckpsnfwrbpqkjpltckx4e

Data Mining Based Marketing Decision Support System Using Hybrid Machine Learning Algorithm

Dr. T. Senthil Kumar
2020 Journal of Artificial Intelligence and Capsule Networks  
This research work proposed a data mining based decision support system using decision tree and artificial neural network as a hybrid approach to estimate the marketing strategies for an organization.  ...  Data mining based decision support system enhances the organization performance by analysing the ground reality.  ...  Based upon the applications, decision support system is categorized into • Data Driven Decision support system, • Communication driven decision support system, • Document driven decision support system  ... 
doi:10.36548/jaicn.2020.3.007 fatcat:kjlcq2httngobo27ypcvprcrq4

Guest Editorial Special Issue on Emerging Computational Intelligence Techniques for Decision Making With Big Data in Uncertain Environments

Weiping Dingr, Nikhil R. Pal, Chin-Teng Lin, Yiu-ming Cheung, Zehong Cao, Wenjian Luo
2021 IEEE Transactions on Emerging Topics in Computational Intelligence  
of data measurement process to name a few.  ...  Special thanks go to the Editor-in-Chief, Prof Yew-Soon Ong, and members of the editorial team for their support during the editing process of this Special Issue.  ... 
doi:10.1109/tetci.2021.3049701 fatcat:fwz2kgi3nnbgvlbednhwelq23i

Optimal Resource Control of Multi-Processor Multi-Radio Nodes Using Semi-Markov Decision Processes

M. Tahir, R. Farrell
2010 2010 IEEE International Conference on Communications  
To achieve our objective, a constrained semi-Markov decision problem is formulated, which not only provides optimal resource control but also meets quality of service demands imposed by application.  ...  An optimal resource control mechanism for a multiprocessor, multi-radio node architecture is proposed.  ...  The authors gratefully acknowledge this support.  ... 
doi:10.1109/icc.2010.5502144 dblp:conf/icc/TahirF10 fatcat:glvr5mlmineljarkvtt2qyqk7q

Diagnostic and Prognostic Models for Predictive Maintenance: Multi-Criteria Comparative Analysis

Mohammed Bouaicha, The National Higher School of Arts and Crafts (ENSAM), Hassan II University, Mers Sultan BP 916, Casablanca, Morocco., Imad El Adraoui, Nadia Machkour, Hassan Gziri, Mourad Zegrari
2021 International Journal of Emerging Technology and Advanced Engineering  
It is therefore developed through a process that begins with the collection of information from the industrial system, the objective of which is its diagnosis or / and its prognosis.  ...  This analysis is based on a multi-criteria comparison of the different models in order to provide a clear vision to choose the appropriate approach for predictive maintenance.  ...  The data analysis and processing process is crucial in a decision support approach in terms of predictive maintenance. These are two main areas: diagnosis and prognosis.  ... 
doi:10.46338/ijetae1021_05 fatcat:4anrz3tdr5ex3glmccgcu4vsbe

Optimization of Multi-Project Environment (OPMPE)

Lokman Hossain, Janaka Ruwanpura
2008 2008 Winter Simulation Conference  
The application and of the model is demonstrated using a collection of real project data for building construction.  ...  The model is capable of analyzing and predicting future problems, assessing the cumulative impact and generates valuable statistics and information for quick decision-making.  ...  ACKNOWLEDGMENTS The authors wish to acknowledge the support and funding for this research project by Ellis Don, Graham, PCL, Ledcor, CANA and Stuart Olson, Construction Research Institute of Canada, Canadian  ... 
doi:10.1109/wsc.2008.4736350 dblp:conf/wsc/HossainR08 fatcat:yt4jevh7ifcf5a7wvbychtt4oy

Condition-Based Maintenance—An Extensive Literature Review

Elena Quatrini, Francesco Costantino, Giulio Di Gravio, Riccardo Patriarca
2020 Machines  
The data-driven bibliometric results have been combined with an interpretative research to extract both core and detailed concepts related to CBM.  ...  The handling of missing data is a crucial aspect for modern CBM implementation and in general for the management of asset-related maintenance, to support CBM decision analysis [66] .  ...  In this way, CBM optimization can be modeled either as a Markov [80, 106] or a semi-Markov decision process [96] . It can also refer to the proportional hazards model [75] .  ... 
doi:10.3390/machines8020031 fatcat:iwvbt5arqfditbreegovxww7te

How are hospitals using artificial intelligence in strategic decision- making?—a scoping review

Sandra G. Leggat, Kevin Yap
2020 Journal of Hospital Management and Health Policy  
This is expected, as it is difficult to assign rules to strategic decision-making suggesting data-driven AI is more appropriate for strategic decision-making (16) .  ...  has repeatable processes for building and deploying analytics; 4, the organization has consistent enterprise-wide processes for analytics; and 5, the enterprise's analytics is strategy driven (62) .  ...  of trust of AI decisions  ... 
doi:10.21037/jhmhp-20-92 fatcat:bbaozae4jve4lj4iiz5aa24lh4

Demystifying Prescriptive Analytics Frameworks and Techniques

2020 VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE  
Big data analytics refers often a very complex process to examine the large and varied data sets to provide the organization to take smarter decisions and better results.  ...  consequences of the decision.  ...  The Cross-Industry standard process for data mining (CRISP-DM) was the rst model to model data mining and business data analytic process.  ... 
doi:10.35940/ijitee.f4546.049620 fatcat:aage3lyfdfc3pfrhmtpv63ciha

Artificial Intelligence Paradigm for Customer Experience Management in Next-Generation Networks: Challenges and Perspectives [article]

Haris Gacanin, Mark Wagner
2018 arXiv   pre-print
We elaborate on data analytics and artificial intelligence driven CEM and their functional differences.  ...  This overview provides a path toward autonomous CEM framework in next-generation networks and sets the groundwork for future enhancements.  ...  Decision networks, decision-theoretic expert system, multiple agents (game theory), Markov decision process, dynamic Bayesian network.  ... 
arXiv:1805.06254v1 fatcat:jhib6jjrqzdjfmsueri64lqgni

Data-driven Task Allocation for Multi-task Transfer Learning on the Edge

Qiong Chen, Zimu Zheng, Chuang Hu, Dan Wang, Fangming Liu
2019 2019 IEEE 39th International Conference on Distributed Computing Systems (ICDCS)  
To solve TATIM with high computational efficiency, we innovatively propose a Data-driven Cooperative Task Allocation (DCTA) approach.  ...  Motivated by the fact that only a few tasks of Multi-task Transfer Learning (MTL) have a higher potential for overall decision performance improvement, we design a novel task allocation scheme, which assigns  ...  Second, decisions made by industrial systems can be highly repetitive, thus generating an abundance of training data to support complicated data-driven model.  ... 
doi:10.1109/icdcs.2019.00107 dblp:conf/icdcs/ChenZHWL19 fatcat:ir7rvngdgnavpcjblwwkavsgpm

Artificial Intelligence and Its Application in Optimization under Uncertainty [chapter]

Saeid Sadeghi, Maghsoud Amiri, Farzaneh Mansoori Mooseloo
2021 Artificial Intelligence  
intelligent decision support systems (DSS).  ...  In this context, the data-driven approach has gained prominence due to its provision of insights for decision-making and easy implementation.  ...  There are two problems in developing a MARL technique for SCM: Building Markov decision processes for a supply chain and then avoiding learning stagnation among agents in learning processes.  ... 
doi:10.5772/intechopen.98628 fatcat:mtbuaqghgvha3fa64osyahca2q

Towards priority-awareness in autonomous intelligent systems

Huma Samin, Luis Hernán García Paucar, Nelly Bencomo, Peter Sawyer
2021 ACM Symposium on Applied Computing  
In this paper, we present a novel use of Multi-Reward Partially Observable Markov Decision Process (MR-POMDP) to support reasoning of separate NFR priorities.  ...  and based on data gathered at runtime.  ...  ACKNOWLEDGMENTS This work has been partially supported by The Lerverhulme Trust Fellowship "QuantUn: quantification of uncertainty using Bayesian  ... 
doi:10.1145/3412841.3442007 dblp:conf/sac/SaminPBS21 fatcat:tprh6llx4jaetcsud5aeoj6onm
« Previous Showing results 1 — 15 out of 21,001 results