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Full-Text Articles in Engineering

Behind Derogatory Migrants' Terms For Venezuelan Migrants: Xenophobia And Sexism Identification With Twitter Data And Nlp, Joseph Martínez, Melissa Miller-Felton, Jose Padilla, Erika Frydenlund Apr 2023

Behind Derogatory Migrants' Terms For Venezuelan Migrants: Xenophobia And Sexism Identification With Twitter Data And Nlp, Joseph Martínez, Melissa Miller-Felton, Jose Padilla, Erika Frydenlund

Modeling, Simulation and Visualization Student Capstone Conference

The sudden arrival of many migrants can present new challenges for host communities and create negative attitudes that reflect that tension. In the case of Colombia, with the influx of over 2.5 million Venezuelan migrants, such tensions arose. Our research objective is to investigate how those sentiments arise in social media. We focused on monitoring derogatory terms for Venezuelans, specifically veneco and veneca. Using a dataset of 5.7 million tweets from Colombian users between 2015 and 2021, we determined the proportion of tweets containing those terms. We observed a high prevalence of xenophobic and defamatory language correlated with the …

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An Algorithm For Finding Data Dependencies In An Event Graph, Erik J. Jensen Apr 2023

An Algorithm For Finding Data Dependencies In An Event Graph, Erik J. Jensen

Modeling, Simulation and Visualization Student Capstone Conference

This work presents an algorithm for finding data dependencies in a discrete-event simulation system, from the event graph of the system. The algorithm can be used within a parallel discrete-event simulation. Also presented is an experimental system and event graph, which is used for testing the algorithm. Results indicate that the algorithm can provide information about which vertices in the experimental event graph can affect other vertices, and the minimum amount of time in which this interference can occur.

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Towards Nlp-Based Conceptual Modeling Frameworks, David Shuttleworth, Jose Padilla Apr 2023

Towards Nlp-Based Conceptual Modeling Frameworks, David Shuttleworth, Jose Padilla

Modeling, Simulation and Visualization Student Capstone Conference

This paper presents preliminary research using Natural Language Processing (NLP) to support the development of conceptual modeling frameworks. NLP-based frameworks are intended to lower the barrier of entry for non-modelers to develop models and to facilitate communication across disciplines considering simulations in research efforts. NLP drives conceptual modeling in two ways. Firstly, it attempts to automate the generation of conceptual models and simulation specifications, derived from non-modelers’ narratives, while standardizing the conceptual modeling process and outcome. Secondly, as the process is automated, it is simpler to replicate and be followed by modelers and non-modelers. This allows for using a common …

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Automatic Generation Of Virtual Work Guide For Complex Procedures: A Case, Shan Liu, Yuzhong Shen Apr 2023

Automatic Generation Of Virtual Work Guide For Complex Procedures: A Case, Shan Liu, Yuzhong Shen

Modeling, Simulation and Visualization Student Capstone Conference

Practical work guides for complex procedures are significant and highly affect the efficiency and accuracy of on-site users. This paper presents a technique to generate virtual work guides automatically for complex procedures. Firstly, the procedure information is extracted from the electronic manual in PDF format. And then, the extracted procedure steps are mapped to the virtual model parts in preparation for animation between adjacent steps. Next, smooth animations of the procedure are generated based on a 3D natural cubic spline curve to improve the spatial ability of the work guide. In addition, each step's annotation is automatically adjusted to improve …

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Enhancing Pedestrian-Autonomous Vehicle Safety In Low Visibility Scenarios: A Comprehensive Simulation Method, Zizheng Yan, Yang Liu, Hong Yang Apr 2023

Enhancing Pedestrian-Autonomous Vehicle Safety In Low Visibility Scenarios: A Comprehensive Simulation Method, Zizheng Yan, Yang Liu, Hong Yang

Modeling, Simulation and Visualization Student Capstone Conference

Self-driving cars raise safety concerns, particularly regarding pedestrian interactions. Current research lacks a systematic understanding of these interactions in diverse scenarios. Autonomous Vehicle (AV) performance can vary due to perception accuracy, algorithm reliability, and environmental dynamics. This study examines AV-pedestrian safety issues, focusing on low visibility conditions, using a co-simulation framework combining virtual reality and an autonomous driving simulator. 40 experiments were conducted, extracting surrogate safety measures (SSMs) from AV and pedestrian trajectories. The results indicate that low visibility can impair AV performance, increasing conflict risks for pedestrians. AV algorithms may require further enhancements and validations for consistent safety performance …

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U-Net Based Multiclass Semantic Segmentation For Natural Disaster Based Satellite Imagery, Nishat Ara Nipa Apr 2023

U-Net Based Multiclass Semantic Segmentation For Natural Disaster Based Satellite Imagery, Nishat Ara Nipa

Modeling, Simulation and Visualization Student Capstone Conference

Satellite image analysis of natural disasters is critical for effective emergency response, relief planning, and disaster prevention. Semantic segmentation is believed to be on of the best techniques to capture pixelwise information in computer vision. In this work we will be using a U-Net architecture to do a three class semantic segmentation for the Xview2 dataset to capture the level of damage caused by different natural disaster which is beyond the visual scope of human eyes.

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Assessing Frustration Towards Venezuelan Migrants In Columbia: Path Analysis On Newspaper Coded Data, Brian Llinás, Guljannat Huseynli, Erika Frydenlund, Katherine Palacia, Jose Padilla Apr 2023

Assessing Frustration Towards Venezuelan Migrants In Columbia: Path Analysis On Newspaper Coded Data, Brian Llinás, Guljannat Huseynli, Erika Frydenlund, Katherine Palacia, Jose Padilla

Modeling, Simulation and Visualization Student Capstone Conference

This study analyzes the impact of Venezuelan migrants on local frustration levels in Colombia. The study found a relationship between the influx of Venezuelan migrants and the level of frustration among locals towards migrants, infrastructure, government, and geopolitics. Additionally, we identified that frustration types have an impact on other frustrations. The study used articles from a national newspaper in Colombia from 2015 to 2020. News articles were coded during a previous study qualitatively and categorized into frustration types. The code frequencies were then used as variables in this study. We used path modeling to statistically study the relationship between dependent …

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Lidar Buoy Detection For Autonomous Marine Vessel Using Pointnet Classification, Christopher Adolphi, Dorothy Dorie Parry, Yaohang Li, Masha Sosonkina, Ahmet Saglam, Yiannis E. Papelis Apr 2023

Lidar Buoy Detection For Autonomous Marine Vessel Using Pointnet Classification, Christopher Adolphi, Dorothy Dorie Parry, Yaohang Li, Masha Sosonkina, Ahmet Saglam, Yiannis E. Papelis

Modeling, Simulation and Visualization Student Capstone Conference

Maritime autonomy, specifically the use of autonomous and semi-autonomous maritime vessels, is a key enabling technology supporting a set of diverse and critical research areas, including coastal and environmental resilience, assessment of waterway health, ecosystem/asset monitoring and maritime port security. Critical to the safe, efficient and reliable operation of an autonomous maritime vessel is its ability to perceive on-the-fly the external environment through onboard sensors. In this paper, buoy detection for LiDAR images is explored by using several tools and techniques: machine learning methods, Unity Game Engine (herein referred to as Unity) simulation, and traditional image processing. The Unity Game …

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From Policy Promotion To Research Output: Brief Analysis Of Technical Challenges Of Hospital-Led Artificial Intelligence Research, Yu Zhuang, Cheng Zhou Apr 2023

From Policy Promotion To Research Output: Brief Analysis Of Technical Challenges Of Hospital-Led Artificial Intelligence Research, Yu Zhuang, Cheng Zhou

Bulletin of Chinese Academy of Sciences (Chinese Version)

In recent years, artificial intelligence has become a key direction of medical and health-related research and a hot spot of international competition. In order to investigate the current situation and challenges in hospital-led artificial intelligence researched, this study selects 14 national pilot hospitals to promote the high-quality development of public hospitals as samples, adopts a combination of quantitative and qualitative methods, analyzes the research articles related to artificial intelligence published by the sample hospitals in recent years, and analyzes the technical challenges in the hospital-led artificial intelligence research. The results show that although the number of hospital-led artificial intelligence research …

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Analysis The Role Of The Internet Of Things And Industry 4.0 In Healthcare Supply Chain Using Neutrosophic Sets, Ahmed M. Abdelmouty, Ahmed Abdel-Monem, Samah Ibrahim Abdel Aal, Mahmoud M. Ismail Apr 2023

Analysis The Role Of The Internet Of Things And Industry 4.0 In Healthcare Supply Chain Using Neutrosophic Sets, Ahmed M. Abdelmouty, Ahmed Abdel-Monem, Samah Ibrahim Abdel Aal, Mahmoud M. Ismail

Neutrosophic Systems with Applications

In today's global economy, the Healthcare supply chain (HCSC) must be aware of a market that is both complicated and ever-changing. The HCSC in Industry 4.0 aims to give patients the medicine they need as quickly and cheaply as possible. The HCSC can improve operations by automating routine tasks and reducing human error by using new technologies like the "Internet of Things" (IoT); so, there is a need to analyze the role of IoT and Industry 4.0 in the Healthcare Supply Chain. This paper aims to analyze the role of IoT and Industry 4.0 in HCSC. Also, this paper proposes …

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Counterventions: A Reparative Reflection On Interventionist Hci, Rua Mae Williams, Louanne E. Boyd, Juan E. Gilbert Apr 2023

Counterventions: A Reparative Reflection On Interventionist Hci, Rua Mae Williams, Louanne E. Boyd, Juan E. Gilbert

Engineering Faculty Articles and Research

Research in HCI applied to clinical interventions relies on normative assumptions about which bodies and minds are healthy, valuable, and desirable. To disrupt this normalizing drive in HCI, we define a “counterventional approach” to intervention technology design informed by critical scholarship and community perspectives. This approach is meant to unsettle normative assumptions of intervention as urgent, necessary, and curative. We begin with a historical overview of intervention in HCI and its critics. Then, through reparative readings of past HCI projects in autism intervention, we illustrate the emergent principles of a counterventional approach and how it may manifest research outcomes that …

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Science Club, Danielle Gibson, Krista Andersen Apr 2023

Science Club, Danielle Gibson, Krista Andersen

Honors Program: Expanded Learning Clubs

Honors After School program for elementary age children to engage with scientific principles. Students performed hands-on experiments to explore various STEM fields. Each weekly lesson consisted of a different concept to be learned or explored by early elementary aged students.

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Earthquake Resistant Buildings, Admin Stem For Success Apr 2023

Earthquake Resistant Buildings, Admin Stem For Success

STEM for Success Showcase

Students learn about earthquakes and engineering by building a structure that can survive an earthquake.

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From Point Estimates To Predictive Distributions In Machine Learning Models - A Statistical Importance Sampling Framework, Giuseppina Carannante Apr 2023

From Point Estimates To Predictive Distributions In Machine Learning Models - A Statistical Importance Sampling Framework, Giuseppina Carannante

Theses and Dissertations

In this thesis, we leverage powerful statistical frameworks for optimal sequential estimation and tracking in non-linear and non-Gaussian dynamical models, which enjoy proven (asymptotic) optimality properties. Initially, we build upon our previous work, which employed first-order Taylor series approximation to propagate the first two predictive moments, to derive Bayesian encoder-decoder networks. This work introduced the notion of dense, pixel-level uncertainty map that is crucial in fields, such as autonomous vehicles and medical segmentation. We then extended the Bayesian framework to an ensembling scheme based on ensemble Kalman Filtering (EnKF). While EnKF represents the predictive distribution with an ensemble of draws, …

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Haptic Systems: Trends And Lessons Learned For Haptics In Spacesuits, Mohammad Amin Kuhail, Jose Berengueres, Fatma Taher, Mariam Alkuwaiti, Sana Z. Khan Apr 2023

Haptic Systems: Trends And Lessons Learned For Haptics In Spacesuits, Mohammad Amin Kuhail, Jose Berengueres, Fatma Taher, Mariam Alkuwaiti, Sana Z. Khan

All Works

Haptic technology uses forces, vibrations, and movements to simulate a sense of touch. In the context of spacesuits, proposals to use haptic systems are scant despite evidence of their efficacy in other domains. Existing review studies have sought to summarize existing haptic system applications. Despite their contributions to the body of knowledge, existing studies have not assessed the applicability of existing haptic systems in spacesuit design to meet contemporary challenges. This study asks, “What can we learn from existing haptic technologies to create spacesuits?”. As such, we examine academic and commercial haptic systems to address this issue and draw insights …

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Designing An Equity-Centered Framework And Crosswalk For Integrated Elementary Computer Science Curriculum And Instruction, Carla Strickland, Andrea Ramírez-Salgado, Lauren Weisberg, Latoya Chandler, Jeanne Di Domenico, Elizabeth M. Lehman, Maya Israel Apr 2023

Designing An Equity-Centered Framework And Crosswalk For Integrated Elementary Computer Science Curriculum And Instruction, Carla Strickland, Andrea Ramírez-Salgado, Lauren Weisberg, Latoya Chandler, Jeanne Di Domenico, Elizabeth M. Lehman, Maya Israel

Journal of Computer Science Integration

As computer science (CS) education becomes more prevalent in K-12 instruction, it is critical for educators, researchers, and curriculum developers to identify culturally responsive and pedagogically inclusive approaches that can increase participation, access, and feelings of belonging for students from historically marginalized communities. In response, we developed an equity-centered curricular framework and illustrative crosswalk that synchronizes three distinct pedagogical approaches: culturally responsive pedagogy (CRP), Universal Design for Learning (UDL), and project-based learning (PBL). We describe the framework’s theoretical underpinnings and explain how this framework informed the development of an integrated elementary science+CS curricular unit and provide examples of its implementation. …

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Rubber Band Car Activity, Admin Stem For Success, Natalie Wilson Apr 2023

Rubber Band Car Activity, Admin Stem For Success, Natalie Wilson

STEM for Success Showcase

Student learn about forces and engineering by designing a car powered by rubber bands

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Femtotesla Magnetometry And Nanoscale Imaging With Color Centers In Diamond, Yaser Silani Apr 2023

Femtotesla Magnetometry And Nanoscale Imaging With Color Centers In Diamond, Yaser Silani

Optical Science and Engineering ETDs

Intriguing photophysical properties of color centers in diamond make them ideal candidates for many applications from imaging and sensing to quantum networking. In the first part of this work, we have studied the silicon vacancy (SiV) centers in diamond for nanoscale imaging applications. We showed that these centers are promising fluorophores for Stimulated Emission Depletion (STED) microscopy, owing to their photostable, near-infrared emission and favorable photophysical properties. In the second part, we built a femtotesla Radio-Frequency (RF) magnetometer based on the diamond nitrogen vacancy (NV) centers and magnetic flux concentrators. We used this sensor to remotely detect Nuclear Quadrupole Resonance …

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Role Of Ai In Threat Detection And Zero-Day Attacks, Kelly Morgan Apr 2023

Role Of Ai In Threat Detection And Zero-Day Attacks, Kelly Morgan

Cybersecurity Undergraduate Research Showcase

Cybercrime and attack methods have been steadily increasing since the 2019 pandemic. In the years following 2019, the number of victims and attacks per hour rapidly increased as businesses and organizations transitioned to digital environments for business continuity amidst lockdowns. In most scenarios cybercriminals continued to use conventional attack methods and known vulnerabilities that would cause minimal damage to an organization with a robust cyber security posture. However, zero-day exploits have skyrocketed across all industries with an increasingly growing technological landscape encompassing internet of things (IoT), cloud hosting, and more advanced mobile technologies. Reports by Mandiant Threat Intelligence (2022) concluded …

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Information Horizon Of Solar Active Regions, Jay R. Johnson, Simon Wing, Carson O'Ffill, Bishwa Neupane Apr 2023

Information Horizon Of Solar Active Regions, Jay R. Johnson, Simon Wing, Carson O'Ffill, Bishwa Neupane

Faculty Publications

Information theory is used to characterize the solar active region periodicities and memories from the Carrington map images 1974–2021. The active regions typically evolve and move from one map to the next. In order to track these active region structures in sequences of images, an innovative method based on information theory is developed. Image entropy provides a measure of the organization of structures in the images. The entropy can also be used as a filter to identify structures and partition the active regions, which are then registered for each image. The partitions are used to compute the mutual information and …

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Removal Of Radionuclides Using Capacitive Deionization, Yusik Won Apr 2023

Removal Of Radionuclides Using Capacitive Deionization, Yusik Won

LSU Doctoral Dissertations

Severe nuclear accidents, including the Fukushima nuclear power plant accident, can lead to the discharge of large amounts of radionuclides into aquatic environments. Some radionuclides such as 137Cs and 90Sr have long half-lives and can remain in the environment for a long period of time. These radionuclides can be detrimental to humans and the environments because they can cause human and environmental exposure to ionizing radiation and because they can be bioaccumulated and biomagnified. Therefore, in case of a severe accident and a radioactive spill, it is important to quickly clean up and treat radioactively contaminated water to …

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Eben Cabs (Mobility As A Service), Asha Kumari Apr 2023

Eben Cabs (Mobility As A Service), Asha Kumari

Manipal Research Colloquium - 2023

Manipal Research Colloquium- 2023 aims to bring students, scholars, and scientists to this forum where discussion on a diverse range of topics from various streams (Health Sciences, Technical Sciences, Basic & Applied Sciences, Humanities & Social Sciences, and Management Sciences) will be taking place.

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Data Analysis On Covid-19 Vaccination In India, Shashank Shekhar, Kumar Abhishek Apr 2023

Data Analysis On Covid-19 Vaccination In India, Shashank Shekhar, Kumar Abhishek

Manipal Research Colloquium - 2023

Manipal Research Colloquium- 2023 aims to bring students, scholars, and scientists to this forum where discussion on a diverse range of topics from various streams (Health Sciences, Technical Sciences, Basic & Applied Sciences, Humanities & Social Sciences, and Management Sciences) will be taking place.

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A Preliminary Study Of The Efficacy Of Using A Wrist-Worn Multiparameter Sensor For The Prediction Of Cognitive Flow States In University-Level Students, Josephine Graft, William Romine, Brooklynn Watts, Noah Schroeder, Tawsik Jawad, Tanvi Banerjee Apr 2023

A Preliminary Study Of The Efficacy Of Using A Wrist-Worn Multiparameter Sensor For The Prediction Of Cognitive Flow States In University-Level Students, Josephine Graft, William Romine, Brooklynn Watts, Noah Schroeder, Tawsik Jawad, Tanvi Banerjee

Computer Science and Engineering Faculty Publications

Engagement is enhanced by the ability to access the state of flow during a task, which is described as a full immersion experience. We report two studies on the efficacy of using physiological data collected from a wearable sensor for the automated prediction of flow. Study 1 took a two-level block design where activities were nested within its participants. A total of five participants were asked to complete 12 tasks that aligned with their interests while wearing the Empatica E4 sensor. This yielded 60 total tasks across the five participants. In a second study representing daily use of the device, …

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A Unified Approach That Makes Online Taxi Service More Effective, Jiyao Li Apr 2023

A Unified Approach That Makes Online Taxi Service More Effective, Jiyao Li

Student Research Symposium

We propose a unified approach for scheduling taxis across a city. Balancing the supplies and demands on a city scale is a challenging problem in the field of online taxi services. To tackle the problem, we design a unified approach considering two important processes: Taxi-Rider Matching and Taxi Guidance. In the Taxi-Rider Matching, with the help of Lottery Selection (LS) and smoothed popularity score, the approach can balance supplies and demands well, both in the local neighborhood areas and hot places across the city. Regarding Taxi Guidance, we propose Q-learning Idle Movement (QIM) to direct vacant taxis to the most …

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High Frequency Radio Communication, Tyler Larsen Apr 2023

High Frequency Radio Communication, Tyler Larsen

Student Research Symposium

This research focuses on high frequency radio communication and its link to space weather. It examines a signal from beacon networks across the globe and analyzes that signal as it arrives to the antennae here at USU. By linking that data to space weather data we can more accurately see how the signal is being affected.

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Dynamic Target Assignment Of Multiple Unmanned Aerial Vehicles Based On Clustering Of Network Nodes, Tuo Zhao, Hanqiang Deng, Jialong Gao, Jian Huang Apr 2023

Dynamic Target Assignment Of Multiple Unmanned Aerial Vehicles Based On Clustering Of Network Nodes, Tuo Zhao, Hanqiang Deng, Jialong Gao, Jian Huang

Journal of System Simulation

Abstract: In order to solve the problem that the distributed multi-UAV target assignment algorithm is prone to communication redundancy, which leads to the large communication scale of formation, a multi-UAV dynamic target assignment algorithm (CU-CBBA) based on node clustering in communication network is proposed.The algorithm introduces the communication network node grouping clustering strategy. According to the node's degree centrality, feature vector centrality, intermediate centrality and other attributes, the network node importance ranking model is established. A group of key nodes in the network topology structure are selected and the network topology node clustering is completed according to the shortest …

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Research On Modeling And Scheduling Of Virtual Power Plant With Dual Demand Response, Qiang Chen, Yi Wang, Kangshun Li Apr 2023

Research On Modeling And Scheduling Of Virtual Power Plant With Dual Demand Response, Qiang Chen, Yi Wang, Kangshun Li

Journal of System Simulation

Abstract: Virtual power plant technology provides an effective means to aggregate distributed power and user side resources to participate in power scheduling. Most of the existing research focus on the scheduling optimization of distributed energy instead of the demand response of user side. The user side resources are divided into contracted reliable response load and non-contracted random response load, and the load response is regulated through price adjustment mechanism to adapt to the change of distributed. A virtual power plant optimal scheduling model with dual demands response is constructed, in which the maximizing overall profit of the power grid is …

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Voltage And Reactive Power Combinational Evaluation Of Regional Power Grid Based On Ewm-Ahp-Bp Neural Network, Yuqi Ji, Huan Xie, Shaoyu Shi, Ping He, Nan Jin, Huili Wang Apr 2023

Voltage And Reactive Power Combinational Evaluation Of Regional Power Grid Based On Ewm-Ahp-Bp Neural Network, Yuqi Ji, Huan Xie, Shaoyu Shi, Ping He, Nan Jin, Huili Wang

Journal of System Simulation

Abstract: In order to quantitatively evaluate the influence of renewable energy access on voltage and reactive power operation, a combinational evaluation method of voltage and reactive power based on EWM-AHP-BP neural network is proposed to carry out the multi-objective evaluation weight calculation. Considering voltage qualified rate, voltage fluctuation, power factor qualified rate and reactive power reserve, the comprehensive evaluation model is established. The operation data of renewable energy and power load are clustered to divide the typical scenarios and the evaluation model under multiple scenarios is scored by the combination method of entropy weight method and analytic hierarchy process. The …

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Research On Modeling And Solution Method Of Operational Tasks Assignment, Yue Ma, Lin Wu, Shengming Guo Apr 2023

Research On Modeling And Solution Method Of Operational Tasks Assignment, Yue Ma, Lin Wu, Shengming Guo

Journal of System Simulation

Abstract: Aiming at the prewar operational tasks assignment in operation task planning, a multi constraint model of operational tasks assignment is constructed to describe the dynamic mapping relationship between operational tasks and operational units. The solution strategy of decision space pruning and constraint condition judgment is proposed, and the methods of decision variable coding, assignment scheme decoding and phased fitness calculation are described. Differential evolution algorithm is used to work out the solution. The experimental results show that the multi constraint assignment model and solution algorithm can effectively reduce the scale of decision space, and can improve the rationality …

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