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Journal articles on the topic 'Scenarios generation'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

Chen, Lijia, Kai Wang, Kezhong Liu, et al. "Combinatorial-Testing-Based Multi-Ship Encounter Scenario Generation for Collision Avoidance Algorithm Evaluation." Journal of Marine Science and Engineering 13, no. 2 (2025): 338. https://doi.org/10.3390/jmse13020338.

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Collision avoidance algorithms play a crucial role in ensuring the safety and effectiveness of autonomous ships, which require comprehensive testing in realistic multi-ship encounter scenarios. However, existing scenario generation methods often inadequately represent the spatiotemporal complexity and dynamic risk interactions of real-world encounters, leading to biased evaluations. To bridge this gap, this paper proposes a combinatorial-testing-based scenario generation framework integrated with spatiotemporal complexity optimisation. First, a full-process scenario representation model is dev

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Syed Abd Mutalib, Sharifah Sakinah, Siti Zanariah Satari, and Wan Nur Syahidah Wan Yusoff. "SYNTHETIC MULTIVARIATE DATA GENERATION PROCEDURE WITH VARIOUS OUTLIER SCENARIOS USING R PROGRAMMING LANGUAGE." Jurnal Teknologi 84, no. 3 (2022): 89–101. http://dx.doi.org/10.11113/jurnalteknologi.v84.17900.

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A synthetic data generation procedure is a procedure to generate data from either a statistical or mathematical model. The data generation procedure has been used in simulation studies to compare statistical performance methods or propose a new statistical method with a specific distribution. A synthetic multivariate data generation procedure with various outlier scenarios using R is formulated in this study. An outlier generating model is used to generate multivariate data that contains outliers. Data generation procedures for various outlier scenarios by using R are explained. Three outlier

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Huang, Wenqi, Lingyu Liang, Zhen Dai, et al. "Scenario Reduction of Power Systems with Renewable Generations Using Improved Time-GAN." Journal of Physics: Conference Series 2662, no. 1 (2023): 012009. http://dx.doi.org/10.1088/1742-6596/2662/1/012009.

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Abstract To investigate the uncertainties and spatiotemporal complexities of renewable energy represented by wind and photovoltaic, a scenario reduction of power systems with renewable generations uses improved time series generative adversarial networks (Time GAN). The long short-term memory neural network is used to construct the generative adversarial networks, and the time-series supervision loss function and generative adversarial loss function are introduced to jointly optimize the generator network for better generating the daily renewable energy power scenarios. Based on the results of

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Saber, Mohammed, Toumi Bouchentouf, and Abdelhamid Benazzi. "Generation of Attack Scenarios for Evaluating IDS." International Journal of Engineering and Technology 4, no. 3 (2012): 298–302. http://dx.doi.org/10.7763/ijet.2012.v4.369.

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Horswill, Ian. "Fiascomatic: A Framework for Automated Fiasco Playsets." Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment 11, no. 3 (2021): 22–29. http://dx.doi.org/10.1609/aiide.v11i3.12823.

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We present Fiascomatic, a mixed initiative system for generating consistent scenarios for the indie storytelling RPG Fiasco. Players can repeatedly generate scenarios, locking down aspects of a scenario they like and regenerating aspects they don’t, until they arrive at a scenario they find entertaining. It is not a story generation system; it generates scenarios from which players then generate stories. Nor is it intended to generate optimal scenarios; it generates random scenarios which the players can then curate according to their taste. Fiascomatic presents an interesting intermediate poi

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Wang, Ziyu, Jing Ma, and Edmund M.-K. Lai. "A Survey of Scenario Generation for Automated Vehicle Testing and Validation." Future Internet 16, no. 12 (2024): 480. https://doi.org/10.3390/fi16120480.

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This survey explores the evolution of test scenario generation for autonomous vehicles (AVs), distinguishing between non-adaptive and adaptive scenario approaches. Non-adaptive scenarios, where dynamic objects follow predetermined scripts, provide repeatable and reliable tests but fail to capture the complexity and unpredictability of real-world traffic interactions. In contrast, adaptive scenarios, which adapt in real time to environmental changes, offer a more realistic simulation of traffic conditions, enabling the assessment of an AV system’s adaptability, safety, and robustness. The shift

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OHNISHI, Atsushi, and Koji KITAMOTO. "A Generation Method of Alternative Scenarios with a Normal Scenario." IEICE Transactions on Information and Systems E93-D, no. 4 (2010): 693–701. http://dx.doi.org/10.1587/transinf.e93.d.693.

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OHNISHI, A. "A Generation Method of Exceptional Scenarios from a Normal Scenario." IEICE Transactions on Information and Systems E91-D, no. 4 (2008): 881–87. http://dx.doi.org/10.1093/ietisy/e91-d.4.881.

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Xiao, Yang, Qinli Xiong, and Kaiwen Pan. "What Is Left for Our Next Generation? Integrating Ecosystem Services into Regional Policy Planning in the Three Gorges Reservoir Area of China." Sustainability 11, no. 1 (2018): 3. http://dx.doi.org/10.3390/su11010003.

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Land use/Land cover (LULC) changes as a result of policy planning influence ecosystem structures, processes, and functions, which are the basis for providing a wide range of ecosystem services (ES). There is an increasing consensus about the importance of integrating ES into ecological policy but quantifying the potential impacts of different policy on ES has proven difficult. We designed a remote sensing, geographic information system and scenario analysis-based approach to estimate and analyze the relationship between ES (soil conservation and carbon sequestration) and ecological policy desi

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Nguyen, V. H. M., L. D. L. Nguyen, C. V. Vo, and B. T. T. Phan. "Green Scenarios for Power Generation in Vietnam by 2030." Engineering, Technology & Applied Science Research 9, no. 2 (2019): 4019–26. https://doi.org/10.5281/zenodo.2647973.

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Energy for future sustainable economic development is considered one crucial issue in Vietnam. This article aims to investigate green scenarios for power generation in Vietnam by 2030. Four scenarios named as business as usual (BAU), low green (LG), high green (HG) and crisis have been proposed for power generation in Vietnam with projection to 2030. Three key factors have been selected for these scenarios, namely: (1) future fuel prices, (2) reduction of load demand caused by the penetration of LED technology and rooftop photovoltaic (PV) systems, and (3) the introduction of power generation

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Nguyen, V. H. M., L. D. L. Nguyen, C. V. Vo, and B. T. T. Phan. "Green Scenarios for Power Generation in Vietnam by 2030." Engineering, Technology & Applied Science Research 9, no. 2 (2019): 4019–26. http://dx.doi.org/10.48084/etasr.2658.

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Energy for future sustainable economic development is considered one crucial issue in Vietnam. This article aims to investigate green scenarios for power generation in Vietnam by 2030. Four scenarios named as business as usual (BAU), low green (LG), high green (HG) and crisis have been proposed for power generation in Vietnam with projection to 2030. Three key factors have been selected for these scenarios, namely: (1) future fuel prices, (2) reduction of load demand caused by the penetration of LED technology and rooftop photovoltaic (PV) systems, and (3) the introduction of power generation

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Ko, Woori, Sangmin Park, Jaewoong Yun, Sungho Park, and Ilsoo Yun. "Development of a Framework for Generating Driving Safety Assessment Scenarios for Automated Vehicles." Sensors 22, no. 16 (2022): 6031. http://dx.doi.org/10.3390/s22166031.

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Despite the technological advances in automated driving systems, traffic accidents involving automated vehicles (AVs) continue to occur, raising concerns over the safety and reliability of automated driving. For the smooth commercialization of AVs, it is necessary to systematically assess the driving safety of AVs under the various situations that they potentially face. In this context, these various situations are mostly implemented by using systematically developed scenarios. In accordance with this need, a scenario generation framework for the assessment of the driving safety of AVs is prop

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Cai, Jinkang, Weiwen Deng, Ying Wang, Haoran Guang, Jiangkun Li, and Juan Ding. "Boundary Scenario Generation for HAVs Based on Classification and Local Sampling." Machines 11, no. 4 (2023): 426. http://dx.doi.org/10.3390/machines11040426.

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High-level Automated Vehicles (HAVs) are expected to improve traffic safety significantly. However, verifying and evaluating HAVs remains an open problem. Scenario-based testing is a promising method for HAV testing. Boundary scenarios exist around the performance boundary between critical and non-critical scenarios. Testing HAVs in these boundary scenarios is crucial to investigate why collisions cannot be avoided due to small changes in scenario parameters. This study proposes a methodology to generate diverse boundary scenarios to test HAVs. First, an approach is proposed to obtain at least

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Pan, Xing, Lunhu Hu, Ziling Xin, Shenghan Zhou, Yanmei Lin, and Yong Wu. "Risk Scenario Generation Based on Importance Measure Analysis." Sustainability 10, no. 9 (2018): 3207. http://dx.doi.org/10.3390/su10093207.

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A risk scenario is a combination of risk events that may result in system failure. Risk scenario analysis is an important part of system risk assessment and avoidance. In engineering activity-based systems, important risk scenarios are related to important events. Critical activities, meanwhile, mean risk events that may result in system failure. This article proposes these definitions of risk event and risk scenario based on the characteristics of risk in engineering activity-based systems. Under the proposed definitions, a risk scenario framework generated based on importance measure analysi

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Dalal, Dhaval, Muhammad Bilal, Hritik Shah, Anwarul Islam Sifat, Anamitra Pal, and Philip Augustin. "Cross-Correlated Scenario Generation for Renewable-Rich Power Systems Using Implicit Generative Models." Energies 16, no. 4 (2023): 1636. http://dx.doi.org/10.3390/en16041636.

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Generation of realistic scenarios is an important prerequisite for analyzing the reliability of renewable-rich power systems. This paper satisfies this need by presenting an end-to-end model-free approach for creating representative power system scenarios on a seasonal basis. A conditional recurrent generative adversarial network serves as the main engine for scenario generation. Compared to prior scenario generation models that treated the variables independently or focused on short-term forecasting, the proposed implicit generative model effectively captures the cross-correlations that exist

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Zhai, Yang, Yufei Zhang, Zhibin Du, et al. "Research on the Data Collection and Scenario Generation Method for Automated Vehicles." Journal of Physics: Conference Series 2665, no. 1 (2023): 012002. http://dx.doi.org/10.1088/1742-6596/2665/1/012002.

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Abstract Automated vehicles should be tested before they can be driven on the road, and the data collection and scenario generation is of great significance for the functional verification and development of automated vehicles. This research focuses on the methods for data collection and scenario generation. The data collection system is established to form industry recognized standards for the data collection. The data collection platform uses vehicles which are equipped with sensors. Based on functions of automated vehicles, functional scenarios, logical scenarios and specific scenarios are

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Chapagain, Kamal, Samundra Gurung, Pisut Kulthanavit, and Somsak Kittipiyakul. "Short-Term Electricity Demand Forecasting Using Deep Neural Networks: An Analysis for Thai Data." Applied System Innovation 6, no. 6 (2023): 100. http://dx.doi.org/10.3390/asi6060100.

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Electricity demand forecasting plays a significant role in energy markets. Accurate prediction of electricity demand is the key factor in optimizing power generation and consumption, saving energy resources, and determining energy prices. However, integrating energy mix scenarios, including solar and wind power, which are highly nonlinear and seasonal, into an existing grid increases the uncertainty of generation, creating additional challenges for precise forecasting. To tackle such challenges, state-of-the-art methods and algorithms have been implemented in the literature. Artificial Intelli

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Zhang, Xuhan, Xiong Wu, Junji Zhou, Dong Liu, Guodong Guo, and Yawei Xue. "A load sequence scenario generation method based on a dual-layer Markov chain Monte Carlo model." Journal of Physics: Conference Series 2896, no. 1 (2024): 012032. https://doi.org/10.1088/1742-6596/2896/1/012032.

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Abstract Generating a large number of representative load sequence scenarios is crucial for evaluating the supply-demand balance, economic efficiency, and reliability of power systems, which have a high penetration rate of new energy. Current scenario generation methods have certain limitations, such as the need for extensive historical data and the inability to reflect the relatively fixed patterns of load sequences over the medium to long term. To address these issues, this paper proposes a load sequence scenario generation method according to a dual-layer Markov chain Monte Carlo (MCMC) mod

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Reis, Andrea Plotzki, Rodrigo Fagundes da Costa, Fabyano Fonseca e. Silva, Fernando Flores Cardoso, and Matthew L. Spangler. "61 The impact of selective phenotyping and genotyping over generations in beef cattle." Journal of Animal Science 97, Supplement_2 (2019): 37–39. http://dx.doi.org/10.1093/jas/skz122.068.

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Abstract The aim of this study was to investigate selective phenotyping to maintain adequate prediction accuracy. A simulation was conducted, with 10 replicates, using QMSim to mimic the structure and size of a Braford population. A population with 50 generations, 500 animals per generation, was created with phenotyping and genotyping beginning in generation 11. The scenarios investigated were: 1) Randomly phenotype and genotype 10, 25, 50, 75, and 100% of individuals each generation and; 2) Randomly phenotype and genotype 10, 25, 50, 75, and 100% of individuals in every-other generation. Esti

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Tu, Zhi, Liangkun Niu, Wei Fan, and Tianyi Zhang. "Multi-modal Traffic Scenario Generation for Autonomous Driving System Testing." Proceedings of the ACM on Software Engineering 2, FSE (2025): 1733–56. https://doi.org/10.1145/3729348.

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Autonomous driving systems (ADS) require extensive testing and validation before deployment. However, it is tedious and time-consuming to construct traffic scenarios for ADS testing. In this paper, we propose TrafficComposer, a multi-modal traffic scenario construction approach for ADS testing. TrafficComposer takes as input a natural language (NL) description of a desired traffic scenario and a complementary traffic scene image. Then, it generates the corresponding traffic scenario in a simulator, such as CARLA and LGSVL. Specifically, TrafficComposer integrates high-level dynamic information

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Gao, Yanna, Hong Dong, Liujun Hu, et al. "A Morphing-Based Future Scenario Generation Method for Stochastic Power System Analysis." Sustainability 16, no. 7 (2024): 2762. http://dx.doi.org/10.3390/su16072762.

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As multiple wind and solar photovoltaic farms are integrated into power systems, precise scenario generation becomes challenging due to the interdependence of power generation and future climate change. Future climate data derived from obsolete climate models, featuring diminished accuracy, less-refined spatial resolution, and a limited range of climate scenarios compared to more recent models, are still in use. In this paper, a morphing-based approach is proposed for generating future scenarios, incorporating the interdependence of power generation among multiple wind and photovoltaic farms u

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Jafer, Shafagh, Bharvi Chhaya, Umut Durak, and Torsten Gerlach. "Automatic Generation of Flight Simulation Scenarios with Aviation Scenario Definition Language." Journal of Aerospace Information Systems 15, no. 4 (2018): 193–202. http://dx.doi.org/10.2514/1.i010514.

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Xu, Zhicheng, Gang Lu, and Jiujin Zhao. "Multi-scenario generation technology considering extreme scenarios in energy system modeling." IOP Conference Series: Earth and Environmental Science 546 (August 12, 2020): 022057. http://dx.doi.org/10.1088/1755-1315/546/2/022057.

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Li, Ning, Lingshan Chen, and Yongchao Huang. "Research on Specific Scenario Generation Methods for Autonomous Driving Simulation Tests." World Electric Vehicle Journal 15, no. 1 (2023): 2. http://dx.doi.org/10.3390/wevj15010002.

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In this paper, we propose a method for the generation of simulated test scenarios for autonomous driving. Based on the requirements of standard regulatory test scenarios, we can generate virtually simulated scenarios and functional scenario libraries for autonomous driving, which can be used for the simulated verification of different ADAS functions. Firstly, the operational design domain (ODD) of a functional scenario is selected, and the weight values of the ODD elements are calculated. Then, a combination test algorithm based on parameter weights is improved to generate virtually simulated

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Fontaine, Matthew C. "Towards Automating the Generation of Human-Robot Interaction Scenarios." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 11 (2022): 12876–77. http://dx.doi.org/10.1609/aaai.v36i11.21575.

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My work studies the problem of generating scenarios to evaluate interaction between humans and robots. I expect these interactions to grow in complexity as robots become more intelligent and enter our daily lives. However, evaluating such interactions only through user studies, which are the de facto evaluation method in human-robot interaction, will quickly become infeasible as the number of possible scenarios grows exponentially with scenario complexity. Therefore, I propose automatically generating scenarios in simulation to explore the diverse possibility space of scenarios to better under

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Freitas, Breno Bezerra, Clayton Ferreira Teles, Davi Ribeiro Lins, et al. "Cenários para a matriz de geração de eletricidade do Ceará em 2050." Ciência e Natura 42 (May 26, 2020): e63. http://dx.doi.org/10.5902/2179460x42805.

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Based on the worldwide proposition of energy matrix scenarios for 2050, the objective of this article is to present scenarios of electricity generation for Ceará in 2050, showing the participation of sources already used in the state's electric matrix and adding new ones. The article proposes three scenarios: a conservative one, where the present proportion of electricity generation sources of the state is maintained, a transitional one, with 50% of electricity generation from non-renewable sources and the other 50% from renewable sources, and 100% renewable, without the use of fossil or nucle

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Ren, Dian, Helai Huang, Ye Li, and Jieling Jin. "High-Risk Test Scenario Generation for Autonomous Vehicles at Roundabouts Using Naturalistic Driving Data." Applied Sciences 15, no. 8 (2025): 4505. https://doi.org/10.3390/app15084505.

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While autonomous vehicles have the potential to mitigate risks associated with dangerous driving behaviors, the safety and stability of autonomous driving technology in real-world applications still require comprehensive tests. Scenario-based virtual simulation testing has emerged as a crucial approach for testing autonomous vehicles, especially in critical scenarios under complex environments, such as merging scenarios at roundabouts with unique traffic features. However, the lack of high-risk scenarios in the real-world traffic domain presents challenges for simulation tests. To address thes

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Anggreeni, Irene, and Mascha C. van der Voort. "Tracing the Scenarios in Scenario-Based Product Design: A Study to Understand Scenario Generation." Design Principles and Practices: An International Journal—Annual Review 2, no. 4 (2008): 123–36. http://dx.doi.org/10.18848/1833-1874/cgp/v02i04/37564.

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Yan, Songyang, Xiaodong Zhang, Kunkun Hao, et al. "On-Demand Scenario Generation for Testing Automated Driving Systems." Proceedings of the ACM on Software Engineering 2, FSE (2025): 86–105. https://doi.org/10.1145/3715722.

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The safety and reliability of Automated Driving Systems (ADS) are paramount, necessitating rigorous testing methodologies to uncover potential failures before deployment. Traditional testing approaches often prioritize either natural scenario sampling or safety-critical scenario generation, resulting in overly simplistic or unrealistic hazardous tests. In practice, the demand for natural scenarios (e.g., when evaluating the ADS's reliability in real-world conditions), critical scenarios (e.g., when evaluating safety in critical situations), or somewhere in between (e.g., when testing the ADS i

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Knies, Christian, and Frank Diermeyer. "Data-Driven Test Scenario Generation for Cooperative Maneuver Planning on Highways." Applied Sciences 10, no. 22 (2020): 8154. http://dx.doi.org/10.3390/app10228154.

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Future automated vehicles will have to meet the challenge of anticipating the intentions of other road users in order to plan their own behavior without compromising safety and efficiency of the surrounding road traffic. Therefore, the research area of cooperative driving deals with maneuver-planning algorithms that enable vehicles to behave cooperatively in interactive traffic scenarios. To prove the functionality of these algorithms, single test scenarios are used in the current body of literature. The use of a single, exemplary scenario bears the risk that the presented approach only works

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Yi, Derong, Mingfeng Yu, Qiang Wang, et al. "Method for Wind–Solar–Load Extreme Scenario Generation Based on an Improved InfoGAN." Applied Sciences 14, no. 20 (2024): 9163. http://dx.doi.org/10.3390/app14209163.

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In recent years, extreme events have frequently occurred, and the extreme uncertainty of the source-demand side of high-ratio renewable energy systems poses a great challenge to the safe operation of power systems. Accurately generating extreme scenarios related to the source-demand side under a high percentage of new power systems is vital for the safe operation of power systems and the assessment of their reliability. However, at this stage, methods for extreme scenario generation that fully consider the correlation between wind power, solar power, and load are lacking. To address these prob

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Cao, Liling, Xinxin Feng, Junli Liu, and Guofeng Zhou. "Automatic Generation System for Autonomous Driving Simulation Scenarios Based on PreScan." Applied Sciences 14, no. 4 (2024): 1354. http://dx.doi.org/10.3390/app14041354.

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The advancement of autonomous driving technology has urgently necessitated enhanced safety testing measures. Traditional road testing methods face significant challenges due to their high costs and prolonged durations. In response to the inefficiencies of manual scenario construction and the difficulties in selecting effective scenarios using common scenario generation methods in autonomous driving safety testing, this study proposes an innovative automatic SG system based on PreScan2021.1.0. The SG process is significantly simplified by this system’s capability to swiftly and accurately gener

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Song, InSung, Seungho Jeon, Donghyun Kim, Min Gyu Lee, and Jung Taek Seo. "GENICS: A Framework for Generating Attack Scenarios for Cybersecurity Exercises on Industrial Control Systems." Applied Sciences 14, no. 2 (2024): 768. http://dx.doi.org/10.3390/app14020768.

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Due to the nature of the industrial control systems (ICS) environment, where process continuity is essential, intentionally initiating a cyberattack to check security controls can cause severe financial and human damage to the organization. Therefore, most organizations operating ICS environments check their level of security through simulated cybersecurity exercises. For these exercises to be effective, high-quality cyberattack scenarios that are likely to occur in the ICS environment must be assumed. Unfortunately, many organizations use limited attack scenarios targeting essential digital a

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Yoo, Jaehyun, Yongju Son, Myungseok Yoon, and Sungyun Choi. "A Wind Power Scenario Generation Method Based on Copula Functions and Forecast Errors." Sustainability 15, no. 23 (2023): 16536. http://dx.doi.org/10.3390/su152316536.

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The scenario of renewable energy generation significantly affects the probabilistic distribution system analysis. To reflect the probabilistic characteristics of actual data, this paper proposed a scenario generation method that can reflect the spatiotemporal characteristics of wind power generation and the probabilistic characteristics of forecast errors. The scenario generation method consists of a process of sampling random numbers and a process of inverse sampling using the cumulative distribution function. In sampling random numbers, random numbers that mimic the spatiotemporal correlatio

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Kichonge, Baraka, Geoffrey R. John, and Iddi S. N. Mkilaha. "Modelling energy supply options for electricity generations in Tanzania." Journal of Energy in Southern Africa 26, no. 3 (2015): 41–57. http://dx.doi.org/10.17159/2413-3051/2015/v26i3a2128.

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The current study applies an energy-system model to explore energy supply options in meeting Tanzania’s electricity demands projection from 2010 to 2040. Three economic scenarios namely; business as usual (BAU), low economic consumption scenario (LEC) and high economic growth scenario (HEC) were developed for modelling purposes. Moreover, the study develops a dry weather scenario to explore how the country’s electricity system would behave under dry weather conditions. The model results suggests: If projected final electricity demand increases as anticipated in BAU, LEC and HEC scenarios, the

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Li, Haoran, Bo Li, and Dongjie Xu. "Transition Pathways to Carbon Neutrality in China's Power System under Multi-Technology Development Scenarios." E3S Web of Conferences 561 (2024): 02007. http://dx.doi.org/10.1051/e3sconf/202456102007.

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This study uses the MESEIC model to design three scenarios of low, middle, and high electricity demand, and three development scenarios of electricity technologies to discuss the development paths of China's future power system to achieve carbon neutrality under different scenarios of electricity demand and electricity development. In the future, China's power system will shift to a new power system mainly based on renewable energy sources, but it is difficult to realize the complete phase-out of coal power under all development scenarios. Under the three scenarios, coal-fired power generation

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Luo, Linbo, Haiyan Yin, Jinghui Zhong, Wentong Cai, Michael Lees, and Suiping Zhou. "Mission-Based Scenario Modeling and Generation for Virtual Training." Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment 9, no. 1 (2021): 44–50. http://dx.doi.org/10.1609/aiide.v9i1.12687.

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Automated scenario generation for virtual training has become an emerging research problem, as manual authoring is often time consuming and costly. In this paper, we present a mission-based scenario modeling and generation framework for virtual training. In particular, we consider the issue of how the timing of the events in a scenario can impact the training process and how to incorporate such impact into the scenario generation. To this end, our framework is designed to explicitly capture the propagated effect of an event and its influence to other events. For representing mission-based scen

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Marcellin, Megan C., Gigi Pavur, John J. Cardenas, et al. "Risk and Systems Analysis for Renewable Power Generation with Environmental and Other Stressors." INCOSE International Symposium 34, no. 1 (2024): 631–48. http://dx.doi.org/10.1002/iis2.13167.

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AbstractThe effects of climate change and water scarcity threaten the stability of critical infrastructure systems in developing regions. In particular, the interconnectedness of energy systems, natural resources, economic growth, and social welfare requires a systems‐level framework to identify scenarios which most impact these systems. This paper evaluates and quantifies infrastructure system risk, defined as the influence of scenarios on system priorities. A scenario‐based multi‐criteria preferences model assesses system component priorities for a baseline scenario as well as climate and re

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Park, Wen, Sung, and Cho. "Multiple Event-Based Simulation Scenario Generation Approach for Autonomous Vehicle Smart Sensors and Devices." Sensors 19, no. 20 (2019): 4456. http://dx.doi.org/10.3390/s19204456.

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Nowadays, deep learning methods based on a virtual environment are widely applied to research and technology development for autonomous vehicle’s smart sensors and devices. Learning various driving environments in advance is important to handle unexpected situations that can exist in the real world and to continue driving without accident. For training smart sensors and devices of an autonomous vehicle well, a virtual simulator should create scenarios of various possible real-world situations. To create reality-based scenarios, data on the real environment must be collected from a real driving

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Zhu, Yu, Jian Wang, Fanqiang Meng, and Tongtao Liu. "Review on Functional Testing Scenario Library Generation for Connected and Automated Vehicles." Sensors 22, no. 20 (2022): 7735. http://dx.doi.org/10.3390/s22207735.

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The advancement of autonomous driving technology has had a significant impact on both transportation networks and people’s lives. Connected and automated vehicles as well as the surrounding driving environment are increasingly exchanging information. The traditional open road test or closed field test, which has large costs, lengthy durations, and few diverse test scenarios, cannot satisfy the autonomous driving system’s need for reliable and safe testing. Functional testing is the emphasis of the test since features such as frontal collision and traffic sign warning influence driving safety.

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Chlebowski, Szymon, Maciej Komosinski, and Adam Kups. "Automated Generation of Erotetic Search Scenarios." ACM Transactions on Computational Logic 18, no. 2 (2017): 1–27. http://dx.doi.org/10.1145/3056537.

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Hidalgo, Ieda Geriberto, Javier Paredes-Arquiola, Joaquin Andreu, Nestor Lerma-Elvira, Joao Eduardo Goncalves Lopes, and Francesco Cioffi. "Hydropower generation in future climate scenarios." Energy for Sustainable Development 59 (December 2020): 180–88. http://dx.doi.org/10.1016/j.esd.2020.10.007.

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Kassem, Y., H. Gokcekus, H. Camur, and A. H. A. Abdelnaby. "Wind Power Generation Scenarios in Lebanon." Engineering, Technology & Applied Science Research 12, no. 6 (2022): 9551–59. http://dx.doi.org/10.48084/etasr.5258.

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Renewable energy in terms of solar and wind energy can be an essential part of Lebanon's strategies to add new capacity, increase energy security, address environmental concerns, and resolve the electricity crisis. In this regard, there is an urgent need to develop road maps in order to reduce the effect of global warming and enhance sustainable technological development for generating clean power in the country. Therefore, the present paper evaluates Lebanon's wind energy generation potential as an alternative solution to supply electricity to households in various locations distributed over

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Rahmanta, Mujammil Asdhiyoga, Rahmat Adiprasetya Al Hasibi, Handrea Bernando Tambunan, et al. "Towards a Net Zero-Emission Electricity Generation System by Optimizing Renewable Energy Sources and Nuclear Power Plant." Energies 17, no. 8 (2024): 1958. http://dx.doi.org/10.3390/en17081958.

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Greenhouse gas emissions, including CO2 emissions, are an issue in the energy sector that must be addressed urgently. The energy sector, including electricity, has been given a global aim of net zero emissions (NZE). This article examines three scenarios for reaching net-zero emissions in power supply. These scenarios are baseline, NZE1, and NZE2. The baseline scenario represents power plant capacity planning based on existing regulations in the base year. The net zero emissions consisting of the NZE1 and NZE2 scenarios aim to achieve net zero emissions by 2060. The NZE1 and NZE2 scenarios dif

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Ramos, Felipe, Regina Mambeli Barros, Geraldo Lúcio Tiago Filho, et al. "Study on the Feasibility of Electricity Generation from Biogas Produced from Municipal Solid Waste and the Biodigestion of Henhouse Manure." Journal of Solid Waste Technology and Management 46, no. 3 (2020): 178–95. http://dx.doi.org/10.5276/jswtm/2020.178.

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Despite consisting of residual material in some processes, solid waste still presents huge potential for recycling, reuse, and energy use, either through thermochemistry or biochemistry. Municipal Solid Waste (MSW) can be energetically exploited by converting landfill gas (LFG) to electrical energy. In addition, animal manure can also undergo biodigestion, generating biogas that can also be harnessed energetically. Achieving economic viability is difficult when evaluating Thermal Power Plants (TPP) using biogas, especially in cases of smaller cities (in the case of LFG) or when animal populati

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Gao , Li, Rui Zhou, and Kai Zhang. "Scenario Generation for Autonomous Vehicles with Deep-Learning-Based Heterogeneous Driver Models: Implementation and Verification." Sensors 23, no. 9 (2023): 4570. http://dx.doi.org/10.3390/s23094570.

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Virtual testing requires hazardous scenarios to effectively test autonomous vehicles (AVs). Existing studies have obtained rarer events by sampling methods in a fixed scenario space. In reality, heterogeneous drivers behave differently when facing the same situation. To generate more realistic and efficient scenarios, we propose a two-stage heterogeneous driver model to change the number of dangerous scenarios in the scenario space. We trained the driver model using the HighD dataset, and generated scenarios through simulation. Simulations were conducted in 20 experimental groups with heteroge

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Ali, Babkir, and Ahmed Gamil. "Scenario-Based Optimization towards Sustainable Power Generation in Sudan." Sustainability 15, no. 20 (2023): 14954. http://dx.doi.org/10.3390/su152014954.

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Sudan faces an electricity supply shortage despite its abundant natural resources. This paper aims to manage these resources for sustainable power generation to meet Sudan’s electricity demand. The sustainability assessment integrates quantitative analysis of power generation’s impacts on water, land, and greenhouse gas (GHG) emissions, in addition to the levelized cost of electricity (LCOE). Cost-effective, resource- and GHG emission-effective, and GHG-stringent scenarios are executed in this study to investigate the impact of different constraints on the sustainability of power generation in

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Ma, Liang, Shigong Jiang, Yi Song, Chenyi Si, and Xiaohan Li. "Multi-Time Scale Scenario Generation for Source–Load Modeling Through Temporal Generative Adversarial Networks." Energies 18, no. 6 (2025): 1462. https://doi.org/10.3390/en18061462.

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With the large-scale integration of distributed power sources, distribution network planning is undergoing significant transformations. To further enhance the efficiency and practicality of distribution network planning, it is essential to model the uncertainties in source–load dynamic scenarios. However, traditional scenario generation methods struggle with high-dimensional variables and complex spatiotemporal characteristics, posing severe challenges for distribution network planning. To address these issues, this paper proposes a multi-time scale source–load scenario generation method based

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Zaame, I., T. Mazri, and A. Elrhayour. "5G: ARCHITECTURE OVERVIEW AND DEPLOYMENTS SCENARIOS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIV-4/W3-2020 (November 23, 2020): 435–40. http://dx.doi.org/10.5194/isprs-archives-xliv-4-w3-2020-435-2020.

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Abstract. Due to the exclusory, growth in the number of connected devices- predicted 50 billion connected devices in 2020 (Gary Davis, 2020) that demand internet access, an upgraded network is required. The fifth generation is the newest mobile network replacing the 4G technology. Deployed from 2020 in many countries, 5G will provide revolutionary innovations in mobile technologies that will reach various high-level goals to the costumers as well as Companies .To benefit from 5G network services, the whole word is growing up rapidly towards the 5G by developing a clear perspective to include t

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Zhang, Delong, Siyu Jiang, Jinxin Liu, et al. "Stochastic Optimization Operation of the Integrated Energy System Based on a Novel Scenario Generation Method." Processes 10, no. 2 (2022): 330. http://dx.doi.org/10.3390/pr10020330.

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The application of integrated energy systems is significant for realizing the comprehensive utilization of various energy sources and improving the utilization rate of renewable energy. At present, the optimal operation of integrated energy systems is a research hotspot. However, shortcomings remain in the stochastic optimization operation and the scenario generation method. This paper proposes a stochastic optimization operation model of an integrated energy microgrid based on an advanced multi-scenario generation method. First, this paper establishes the time-divided probability distribution

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