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2021

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Articles 661 - 690 of 844

Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering

Efficient Real-Time Traffic Signal Control Algorithm, Zhongcheng Yang, Ye Chen, Zhenyu Yang Jan 2021

Efficient Real-Time Traffic Signal Control Algorithm, Zhongcheng Yang, Ye Chen, Zhenyu Yang

Journal of System Simulation

Abstract: For real time taffic signal contol isus, a mathematical model was proposed to minimize the waiting ime, meanwhile a huristi search aigorihm was given to sove the optinal sluton Simulatin Tresuts show that the hcurisi scarceh algorim sufrfs fom being couataoalal complx and umstable, therefore, a multi sage decisin optimization algorihm is added, and the serehes adopt in all stages subject to a time limit, which ensures a stable and real-time algorithm, and also a soution in fixed time. Simulation resuts based on actal tafic data show that the waiting time can be reduced in comparison with that of …

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Modeling Emergence Of Network Radar Countermeasure System, Huang Chen, Jianqing Qi, Fangzheng Liu Jan 2021

Modeling Emergence Of Network Radar Countermeasure System, Huang Chen, Jianqing Qi, Fangzheng Liu

Journal of System Simulation

Abstract: Network radar countermeasure system (NRCS) is a new kind of integrated electronic warfare system with the integrated network developing trend of radar and EW equipment, and emergence is the typical complex feature of NRCS. The connotation and composition of the NRCS emergence was interpreted. Four sources of the NRCS emergence were analyzed: composition effect, structural effect, interaction effect and environmental effect. The conceptual models and mathematical models of the NRCS emergence were built from three aspects: system reconnaissance detection emergence, system target identification emergence and system jamming emergence. Simulation results coincide with the NRCS emergence source analysis, which verifies …

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Simulation Of Energy Optimization For Cooling Coil In Central Air-Conditioning System, Qinglong Meng, Xiuying Yan Jan 2021

Simulation Of Energy Optimization For Cooling Coil In Central Air-Conditioning System, Qinglong Meng, Xiuying Yan

Journal of System Simulation

Abstract: The optimized control of minimizing energy consumption in one air-conditioning system was studied. The main models that needed in the simulation software HVACSIM+ for air handling unit were introduced. The AHU and rooms of the first floor of certain Building were taken as the simulation target. Then the function describing the relation between the consumption of cooling coil and the chilled water velocity was found and taken as the objective function. With improved cyclic variable method, the controller^ parameters were optimized. Results show that the simulation system runs steadily while the controller works with the optimal parameters, and the …

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Gait Simulation Of Snake Robot Based On Cpg Method, Gao Qin, Zhelong Wang, Weijian Hu, Lanying Zhao Jan 2021

Gait Simulation Of Snake Robot Based On Cpg Method, Gao Qin, Zhelong Wang, Weijian Hu, Lanying Zhao

Journal of System Simulation

Abstract: Biological snakes in nature have a variety of periodic motion patterns such as serpentine motion, linear motion and lateral motion. Gaits diversity has greatly improved the adaptability of natural snakes to complex environment. Biologists has proved that such rhythmic movements of vertebrate animals are generated by CPG (the central neural pattern generator). Special mechanical structure of a snake robot with high degree offreedom and locomotion characteristics of different gaits was considered to bulid a suitale CPG network model. Hopf oscillators were chosen as neuron models of a central pattern generator owing to their stable features. A snake robot prototype …

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Optimized Analysis Of Milling Thin-Wall Parts Based On Shell Element Models, Yusong Liao, Han Jiang Jan 2021

Optimized Analysis Of Milling Thin-Wall Parts Based On Shell Element Models, Yusong Liao, Han Jiang

Journal of System Simulation

Abstract: As to milling the thin-wall part accurately, here with the finite element model composed of SHELL elements, the effects of lowering position, size of the part and cutting parameters to the deformations of the thin-wall part were analyzed and compared, and the corresponding theoretical analysis was provided. The conclusions can be got as; the model composed of SHELL elements can analyze the factors causing the deforroations of the thin-wall part and optimize the cutting method and cutting parameters effectively to improve the machining accuracy and efficiency.

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Modeling And Simulation Of Traction System In Hybrid Shunting Locomotive, Kun Shen, Wang Ling, Wang Jian, Xiaoyang Yao Jan 2021

Modeling And Simulation Of Traction System In Hybrid Shunting Locomotive, Kun Shen, Wang Ling, Wang Jian, Xiaoyang Yao

Journal of System Simulation

Abstract: The structure of traction system in hybrid shunting locomotive was analyzed, and the working principles of traction system under multiform power models were introduced. Based on which, the models of traction system and power accumulators of this hybrid shunting locomotive were built by MATLAB/Simulink, then the simulation experiments on hybrid shunting locomotive with the power models of hybrid power, and pure diesel generator power or pure accumulator power were done respectively. The simulation results show that hybrid shunting locomotive can achieve reliable operation in diflFerent conditions by the designed main circuit structure, parameters and system energy management strategy.

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Impact Of Number Of Solar Cells In Parallel/Series And Temperature On Junction Capacitance, Zhigang Zhao, Chunjie Zhang, Gao Pu, Hutang Sang, Xiaoqian Li Jan 2021

Impact Of Number Of Solar Cells In Parallel/Series And Temperature On Junction Capacitance, Zhigang Zhao, Chunjie Zhang, Gao Pu, Hutang Sang, Xiaoqian Li

Journal of System Simulation

Abstract: The study to the dynamic parameters of the photovoltaic cell is of crucial importance for the design of the corresponding afterward stage controller in the photovoltaic power generation system. Beginning with the analysis to physical mechanism of the photovoltaic cell, more accurate equivalent formulation of the junction voltage and bias voltage of the photovoltaic cells /module/array was deduced, and the explicit formulation between the bias voltage and output voltage was received by using the Lambert W function based on equivalent series resistance and the saturation current. The formulation was adopted which combined the engineering mathematics model and intrinsic carrier …

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Evaluation And Analysis Of New Method Of Measurement Of Target Scattering Matrix, Zhenyu Huang, Zhao Bo, Huanyao Dai, Liandong Wang, Xuequan Zhou Jan 2021

Evaluation And Analysis Of New Method Of Measurement Of Target Scattering Matrix, Zhenyu Huang, Zhao Bo, Huanyao Dai, Liandong Wang, Xuequan Zhou

Journal of System Simulation

Abstract: The basic theory of radar polarization signal processing is measurement of the target scattering matrix. The current algorithm of measurement of the target scattering matrix is gotten through orthogonal dual polarization channel in time-sharing or simultaneously, which demands orthogonal polarization measurement signals with complex coding. The measuring accuracy is higher. The complexity and the cost of the system are relatively higher. Scattering matrix can also be obtained by making use of the spatial polarization characteristics of the antenna to processing the radar echo without structure reformation of the radar. It only. needs to renewal measurement technology. The comparison and …

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The Effects Of Customer Segmentation, Borrowers' Behaviours And Analytical Methods On The Performance Of Credit Scoring Models In The Agribusiness Sector, Daniela Lazo, Raffaella Calabrese, Cristian Bravo Roman Jan 2021

The Effects Of Customer Segmentation, Borrowers' Behaviours And Analytical Methods On The Performance Of Credit Scoring Models In The Agribusiness Sector, Daniela Lazo, Raffaella Calabrese, Cristian Bravo Roman

Statistical and Actuarial Sciences Publications

The main aim of this study is to analyse the joint effects of customer segmentation, borrowers' characteristics and modelling techniques on the classification accuracy of a scoring model for agribusinesses. To this end, we used data provided by a Chilean company on 161,163 loans from January 2007 to December 2013. We considered random forest, neural network and logistic regression models as analytical methods. Regarding the borrowers' profiles, we examined the effects of socio-demographic, repayment-behaviour, agribusiness-specific and credit-related variables. We also segmented the customers as individuals, SMEs and large holdings. As the segments show different risk behaviours, we obtained a better …

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Adaptive Task Allocation In Automated Vehicles, Skye Taylor, Bin Hu, Jing Chen Jan 2021

Adaptive Task Allocation In Automated Vehicles, Skye Taylor, Bin Hu, Jing Chen

Psychology: Interdisciplinary Research in Behavioral Sciences of Transportation Issues

Adaptive task allocation is used in many human-machine systems and has been proven to improve operators’ monitoring and/or performance with automated systems. However, there is little knowledge surrounding the benefits of adaptive task allocation in automated vehicles. In this study, participants were presented with media depicting driving scenarios of both low and high workload at two levels of automation. The participants reported which tasks they felt comfortable allocating to themselves or to the automated system in each driving scenario, as well as whether they would conduct the task allocation manually or have the automated system automatically allocate the tasks. The …

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Creating A Driving Workload Model And Identifying Best Practices, Josalin Kumm, Holly Handley, Yusuke Yamani Jan 2021

Creating A Driving Workload Model And Identifying Best Practices, Josalin Kumm, Holly Handley, Yusuke Yamani

Psychology: Interdisciplinary Research in Behavioral Sciences of Transportation Issues

One major way to investigate distracted driving is to have drivers engage in a secondary task. Driving models are one way to better understand workload during driving which could result in safer driving. During this study, we create a driving model using cognitive task analysis software to analyze workload with N-Back tasks. N-Back task requires the driver to memorize and repeat numbers and letters. The result will help us determine if we can continue using this software in future research and analysis workload in a scenario with secondary tasks by comparing it to other analysis software in the framework of …

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Asset Management Framework For The United States Army Corps Of Engineers Lock And Dam Electrical Equipment, Megan Elizabeth Bates Jan 2021

Asset Management Framework For The United States Army Corps Of Engineers Lock And Dam Electrical Equipment, Megan Elizabeth Bates

Theses, Dissertations and Capstones

The focus of this thesis is to design an efficient and effective preventative maintenance program for the electrical equipment that the United States Army Corps of Engineers (USACE) operates at the locks and dams. This thesis presents the concept of asset management and designs a framework to manage the electrical assets at USACE. The methodology was tested, and the results validated the framework proposed in this thesis. The framework was tested on two separate projects and the results were the same optimized strategies, which shows that the framework is robust and can be implemented into each project and can give …

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Queueing Models With Map Arrivals Useful In Service Sectors, Srinivas R. Chakravarthy Jan 2021

Queueing Models With Map Arrivals Useful In Service Sectors, Srinivas R. Chakravarthy

Industrial & Manufacturing Engineering Publications

Queueing models have found applications in many fields, notably in service sectors. In this paper, we study queueing models that have significant applications in service sectors. We look at multi-server systems with MAP arrivals. We assume phase type services for single server systems and exponential services when dealing with multi-server systems. All arriving customers finding no idle server will not wait in the system to receive services but rather leave their information in a registry list. These customers will be reached out on a first-come-first-served basis (FCFS) by an idle server soon after completing its current service. The reach out …

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Application Of Analogical Reasoning For Use In Visual Knowledge Extraction, Kara Lian Combs Jan 2021

Application Of Analogical Reasoning For Use In Visual Knowledge Extraction, Kara Lian Combs

Browse all Theses and Dissertations

There is a continual push to make Artificial Intelligence (AI) as human-like as possible; however, this is a difficult task because of its inability to learn beyond its current comprehension. Analogical reasoning (AR) has been proposed as one method to achieve this goal. Current literature lacks a technical comparison on psychologically-inspired and natural-language-processing-produced AR algorithms with consistent metrics on multiple-choice word-based analogy problems. Assessment is based on “correctness” and “goodness” metrics. There is not a one-size-fits-all algorithm for all textual problems. As contribution in visual AR, a convolutional neural network (CNN) is integrated with the AR vector space model, Global …

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Intelligent Healthcare Process Discovery And Operational Coordination Using Discrete Event Simulation And Machine Learning, Suleyman Yildirim Jan 2021

Intelligent Healthcare Process Discovery And Operational Coordination Using Discrete Event Simulation And Machine Learning, Suleyman Yildirim

Wayne State University Dissertations

The healthcare system in the US is rapidly changing and reshaping to adopt continuously evolving demand for improved operational efficiency and treatment effectiveness from patients and providers in critical health services. Healthcare service systems and clinical treatment operations need to be more predictable to increase operational efficiency through proactive operations management. This research contributes to the literature by discovering clinical processes and calibrating discrete-event simulation models in healthcare service systems using data-driven and process-driven predictive models. Unlike the data-driven predictive approaches such as machine learning and statistical methods, the proposed methodologies in this thesis leverages and focuses on process-based methods …

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Medical Surge Capability: Performance Modeling Of Hospital Emergency Departments, Egbe-Etu Emmanuel Etu Jan 2021

Medical Surge Capability: Performance Modeling Of Hospital Emergency Departments, Egbe-Etu Emmanuel Etu

Wayne State University Dissertations

Hospitals are faced with significant challenges during and after natural or human-caused disasters. Surge planning is a critical component of every healthcare facility’s emergency plan and response system. The process of managing and allocating scarce resources by tackling the vulnerability inherent to patients means that defining improvement priorities is one of the main challenges healthcare systems face when responding to a medical surge event (e.g., COVID-19). The consequences of these challenges include increased patient mortality, ambulance diversion, long wait times, and unavailability of beds. Previous efforts in hospital operations management have successfully applied operations research techniques in analyzing and optimizing …

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A Multi-Agent Semi-Cooperative Unmanned Air Traffic Management Model With Separation Assurance, Yanchao Liu Jan 2021

A Multi-Agent Semi-Cooperative Unmanned Air Traffic Management Model With Separation Assurance, Yanchao Liu

Industrial and Systems Engineering Faculty Research Publications

This paper presents an air traffic management framework to enable multiple fleets of unmanned aerial vehicles to traverse dense, omni-directional air traffic safely and efficiently. The main challenge addressed here is separation assurance in the absence of full coordination and communication. In this framework, each fleet is independently managed by a routing agent, which progressively plans the non-overlapping move-ahead corridors for vehicles in the fleet by solving a nonlinear optimization model. The model is artfully designed so that agents of different fleets need not engage in complicated multilateral communications or make guesses about external vehicles’ flight intents to maintain effective …

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Application Of Analogical Reasoning For Use In Visual Knowledge Extraction, Kara Lian Combs Jan 2021

Application Of Analogical Reasoning For Use In Visual Knowledge Extraction, Kara Lian Combs

Browse all Theses and Dissertations

There is a continual push to make Artificial Intelligence (AI) as human-like as possible; however, this is a difficult task because of its inability to learn beyond its current comprehension. Analogical reasoning (AR) has been proposed as one method to achieve this goal. Current literature lacks a technical comparison on psychologically-inspired and natural-language-processing-produced AR algorithms with consistent metrics on multiple-choice word-based analogy problems. Assessment is based on “correctness” and “goodness” metrics. There is not a one-size-fits-all algorithm for all textual problems. As contribution in visual AR, a convolutional neural network (CNN) is integrated with the AR vector space model, Global …

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Identifying Sources Of Covid19 Pandemic Supply Chain Fragility, Clovia Hamilton Jan 2021

Identifying Sources Of Covid19 Pandemic Supply Chain Fragility, Clovia Hamilton

Technology & Society Faculty Publications

Supply chain management is in the industrial engineering management and operations management disciplines. It involves product procurement of raw materials, production, storage, distribution, wholesales, and retail sales. The COVID19 pandemic has the added challenge of healthcare service operations management. This paper is a bibliometric study of the COVID19 supply chain fragility problem. In February 2021, the United States’ President called for a review of the pandemic related supply chain for vaccines, personal protective equipment (PPE), medical equipment such as ventilators, and food. This study involves a search for references published between January 1, 2020 and April 30, 2021. It reveals …

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Computational Modeling For Decision-Making Under Climate Change Uncertainty: Reservoir Simulation Game, Julianne Quinn Jan 2021

Computational Modeling For Decision-Making Under Climate Change Uncertainty: Reservoir Simulation Game, Julianne Quinn

All ECSTATIC Materials

Almost every decision you make is under uncertainty. Will I need a rain jacket in the afternoon? Will they say yes if I ask them out? Is 1 hour enough time to finish this assignment? Oftentimes, we can use computational modeling to simulate different scenarios of what might happen in the future to inform what decisions are best on average, or what decisions minimize the worst case outcome. For example, you could decide what player to draft for your Fantasy Football team by simulating player performance. In this activity, we will simulate how much water to release from a dam …

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Methods To Integrate Domain Expert User Knowledge Into Process Discovery, Jasim Alnahas Jan 2021

Methods To Integrate Domain Expert User Knowledge Into Process Discovery, Jasim Alnahas

Wayne State University Dissertations

Process Mining (PM) is a new era in business development management that reinforces business process sustainability. Process Mining uses various techniques to discover the process model and identify the root cause analysis of process delays based on the event log. There are three main types of process models: procedural models, declarative models, and hybrid models. Procedural models tend to discover the main pattern of the activity flows in the process. In contrast, declarative models analyze the process behavior and express this behavior as a compact set of rules between pair of two activities. Hybrid models are a combination of procedural …

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The Architecture Design Of Electrical Vehicle Infrastructure Using Viable System Model Approach, Mahdi Boucetta, Niamat Ullah Ibne Hossain, Raed Jaradat, Charles Keating, Siham Tazzit, Morteza Nagahi Jan 2021

The Architecture Design Of Electrical Vehicle Infrastructure Using Viable System Model Approach, Mahdi Boucetta, Niamat Ullah Ibne Hossain, Raed Jaradat, Charles Keating, Siham Tazzit, Morteza Nagahi

Engineering Management & Systems Engineering Faculty Publications

Exponential technological-based growth in industrialization and urbanization, and the ease of mobility that modern motorization offers have significantly transformed social structures and living standards. As a result, electric vehicles (EVs) have gained widespread popularity as a mode of sustainable transport. The increasing demand for of electric vehicles (EVs) has reduced the some of the environmental issues and urban space requirements for parking and road usage. The current body of EV literature is replete with different optimization and empirical approaches pertaining to the design and analysis of the EV ecosystem; however, probing the EV ecosystem from a management perspective has not …

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Effective Project Management And The Role Of Quality Assurance Throughout The Project Life Cycle, Monier Madison Ouabira, Hengameh Fakhravar Jan 2021

Effective Project Management And The Role Of Quality Assurance Throughout The Project Life Cycle, Monier Madison Ouabira, Hengameh Fakhravar

Engineering Management & Systems Engineering Faculty Publications

Quality is a fundamental requirement in effective project management. Effective project management entails a steady focus on quality management as well as achievement of all user requirements as defined during the requirements engineering phase of project implementation. Quality assurance must be executed throughout the project development cycle as a new normal in reducing errors and challenges during project development. Conducting quality assurance throughout the project development cycle has many benefits to both the project as well as the project development team. Understanding the research approach to use is critical in achieving high-quality findings in projects. There is a need to …

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Complex System Governance As A Framework For Asset Management, Polinpapilinho F. Katina, James C. Pyne, Charles B. Keating, Dragan Komljenovic Jan 2021

Complex System Governance As A Framework For Asset Management, Polinpapilinho F. Katina, James C. Pyne, Charles B. Keating, Dragan Komljenovic

Engineering Management & Systems Engineering Faculty Publications

Complex system governance (CSG) is an emerging field encompassing a framework for system performance improvement through the purposeful design, execution, and evolution of essential metasystem functions. The goal of this study was to understand how the domain of asset management (AsM) can leverage the capabilities of CSG. AsM emerged from engineering as a structured approach to organizing complex organizations to realize the value of assets while balancing performance, risks, costs, and other opportunities. However, there remains a scarcity of literature discussing the potential relationship between AsM and CSG. To initiate the closure of this gap, this research reviews the basics …

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The Technology Transfer Network Dynamic In The Information Technology Industry Of Yucatan, Mexico, Francisco Cima, Pilar Pazos, Ana Maria Canto Jan 2021

The Technology Transfer Network Dynamic In The Information Technology Industry Of Yucatan, Mexico, Francisco Cima, Pilar Pazos, Ana Maria Canto

Engineering Management & Systems Engineering Faculty Publications

The present paper explores the technology transfer linkages among universities, research centers, and private companies in Yucatan, Mexico's information technology industry. Social network analysis (SNA) was used as a method to identify the structural characteristics of the technology transfer collaborations, and the changes in the patterns of interactions among institutions over the years. Data were obtained from the National Council for Science and Technology repository (CONACYT). Associations formed to enhance technology advancement and innovation practices between 2010 and 2018 were analyzed in this study. Network transitivity, the patterns of triadic configurations, and heterophily were compared to uncover the evolution of …

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Interactive Agent-Based Simulation For Experimentation: A Case Study With Cooperatve Game Theory, Andrew J. Collins, Sheida Etemadidavan Jan 2021

Interactive Agent-Based Simulation For Experimentation: A Case Study With Cooperatve Game Theory, Andrew J. Collins, Sheida Etemadidavan

Engineering Management & Systems Engineering Faculty Publications

Incorporating human behavior is a current challenge for agent-based modeling and simulation (ABMS). Human behavior includes many different aspects depending on the scenario considered. The scenario context of this paper is strategic coalition formation, which is traditionally modeled using cooperative game theory, but we use ABMS instead; as such, it needs to be validated. One approach to validation is to compare the recorded behavior of humans to what was observed in our simulation. We suggest that using an interactive simulation is a good approach to collecting the necessary human behavior data because the humans would be playing in precisely the …

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Human Characteristics Impact On Strategic Decisions In A Human-In-The-Loop Simulation, Andrew J. Collins, Shieda Etemadidavan Jan 2021

Human Characteristics Impact On Strategic Decisions In A Human-In-The-Loop Simulation, Andrew J. Collins, Shieda Etemadidavan

Engineering Management & Systems Engineering Faculty Publications

In this paper, a hybrid simulation model of the agent-based model and cooperative game theory is used in a human-in-the-loop experiment to study the effect of human demographic characteristics in situations where they make strategic coalition decisions. Agent-based modeling (ABM) is a computational method that can reveal emergent phenomenon from interactions between agents in an environment. It has been suggested in organizational psychology that ABM could model human behavior more holistically than other modeling methods. Cooperative game theory is a method that models strategic coalitions formation. Three characteristics (age, education, and gender) were considered in the experiment to see if …

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Dynamic Analysis Of The Implementation Of The Blockchain Technology In The Supply Chain, Rehab Ali Jan 2021

Dynamic Analysis Of The Implementation Of The Blockchain Technology In The Supply Chain, Rehab Ali

Electronic Theses and Dissertations, 2020-2023

Blockchain technology is a new digital technology that has been disrupting the way businesses are performing. It is a decentralized and distributed ledger that enables transactions of any form of value. As blockchain technology provides visibility, transparency, and security through the multi-agent system, the supply chain sector is one of its critical and promising applications. In a highly dynamic environment, the supply chain's efficiency needs to be measured from a blockchain perspective. As the main benefit of blockchain technology is the visibility and real-time access to data, blockchain technology's preeminent affected areas within the supply chain are the responsiveness to …

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A Multi-Elm Model For Incomplete Data, Baichuan Chi, Amaury Lendasse, Edward Ratner, Renjie Hu Jan 2021

A Multi-Elm Model For Incomplete Data, Baichuan Chi, Amaury Lendasse, Edward Ratner, Renjie Hu

Engineering Management and Systems Engineering Faculty Research & Creative Works

This Paper Presents a Novel Model of Extreme Learning Machines (Elms) for Incomplete Data. Elms Are Fast Accurate Randomized Neural Networks. Nevertheless, Elm Can Only Be Applied on the Complete Dataset. Therefore, a Novel Multi-Elm Model for Incomplete Data is Proposed, Consisting of Multiple Secondary Elms and One Primary Elm. the Secondary Elms Are Approximating the Primary Elm's Hidden Neurons' Outputs for the Data with Missing Values. as Summarized in the Experimental Section, This Model Can Be Applied on Data with Any Missing Patterns, without using Imputations and Can Outperform the Traditional Imputation Methods within a Reasonable Fraction of Missing …

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Integrated Optimization And Learning Methods Of Predictive And Prescriptive Analytics, Mehmet Kolcu Jan 2021

Integrated Optimization And Learning Methods Of Predictive And Prescriptive Analytics, Mehmet Kolcu

Wayne State University Dissertations

A typical decision problem optimizes one or more objectives subject to a set of constraints on its decision variables. Most real-world decision problems contain uncertain parameters. The exponential growth of data availability, ease of accessibility in computational power, and more efficient optimization techniques have paved the way for machine learning tools to effectively predict these uncertain parameters. Traditional machine learning models measure the quality of predictions based on the closeness between true and predicted values and ignore decision problems involving uncertain parameters for which predicted values are treated as the true values.Standard approaches passing point estimates of machine learning models …

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