Agent Based Model to Analyze Consumer Behavior in Consuming the Electricity Energy

2015 ◽  
Vol 72 (4) ◽  
Author(s):  
Erma Suryani ◽  
Rully Agus Hendrawan ◽  
Umi Salama ◽  
Lily Puspa Dewi

Several studies have been conducted regarding save energy in consuming the electricity through the simple changes in routines and habits. In the case of electricity consumption, consumer behavior might influenced by several factors such as consumer profession, season, and environmental awareness. In this paper, we developed an Agent Based Model (ABM) to analyze the behavior of different agents in consuming the electricity energy for each type of profession (agent) as well as their interaction with the environment. This paper demonstrates a prototype agent based simulation model to estimate the electricity consumption based on the existing condition and some scenarios to reduce the electricity consumption from consumer point of view. From the scenario results, we analyzed the impact of the save energy to increase the electrification ratio. 

2020 ◽  
Vol 88 ◽  
pp. 8-28
Author(s):  
Rimvydas Laužikas ◽  
Darius Plikynas ◽  
Vytautas Dulskis ◽  
Leonidas Sakalauskas ◽  
Arūnas Miliauskas

The impact of cultural processes on personal and social changes is one of the important research issues not only in contemporary social sciences but also for simulation of future development scenarios and evidence-based policy decision making. In the context of the theoretical concept of cultural values, based on the system theory and theory of social capital, the impact of cultural events could be analyzed and simulated by focussing on the construction/deconstruction of social capital, which takes place throughout the actor’s cultural participation. The main goal of this research is the development of measuring metrics, and agent-based simulation model aimed at investigation of the social impact of cultural processes.  This paper provides new insights of modeling the social capital changes in a society and its groups, depending on cultural participation. The proposed measurement metrics provide the measurement facility of three key components: actors, cultural events and events flow and social capital. It provides the initial proof of concept simulation results, - simplified agent-based simulation model showcase. The NetLogo MAS platform is used as a simulation environment.  


2019 ◽  
Vol 18 (06) ◽  
pp. 1909-1939
Author(s):  
Heng Du ◽  
Tiaojun Xiao

This paper examines pricing strategies for two adaptive retailers competing on two products in the presence of complex consumer behavior, where consumers own heterogeneous product and store valuations and the number of potential consumers is random. Each retailer can choose one from two pricing strategies: the uniform pricing format (offering the same price for two products) or the differentiated pricing format (offering different prices). Utilizing agent-based model (each retailer is modeled as an autonomous agent with the reinforcement learning behavior), we find that: (i) the differentiated pricing format is not always the optimal choice; (ii) when the uncertainty of one product/store valuation is a little larger than that of the rival, both retailers should adopt uniform pricing. Besides, when wholesale price contract is endogenous, we find that supplier’s pricing behavior can change the impact of the fixed cost on the pricing strategy.


2021 ◽  
Author(s):  
Kashif Zia

In this paper, an Agent-Based Model (ABM) is proposed to evaluate the impact of COVID-19 vaccination drive in different settings. The main focus is to evaluate the counter-effectiveness of disparity in vaccination drive among different regions/countries. The model proposed is simple yet novel in the sense that it captures the spatial transmission-induced activity into consideration, through which we are able to relate the transmission model to the mutated variations of the virus. Some important what-if questions are asked in terms of the number of deaths, and time required and the percentage of the population needed to be vaccinated before the pandemic is eradicated. The simulation results have revealed that it is necessary to maintain a global (rather than regional or country-oriented) vaccination drive in case of a new pandemic or continual efforts against COVID-19.


2021 ◽  
Vol 28 (1) ◽  
Author(s):  
Daniel Honsel ◽  
Verena Herbold ◽  
Stephan Waack ◽  
Jens Grabowski

AbstractTo guide software development, the estimation of the impact of decision making on the development process can be helpful in planning. For this estimation, often prediction models are used which can be learned from project data. In this paper, an approach for the usage of agent-based simulation for the prediction of software evolution trends is presented. The specialty of the proposed approach lies in the automated parameter estimation for the instantiation of project-specific simulation models. We want to assess how well a baseline model using average (commit) behavior of the agents (i.e., the developers) performs compared to models where different amount of project-specific data is fed into the simulation model. The approach involves the interplay between the mining framework and simulation framework. Parameters to be estimated include, e.g., file change probabilities of developers and the team constellation reflecting different developer roles. The structural evolution of software projects is observed using change coupling graphs based on common file changes. For the validation of simulation results, we compare empirical with simulated results. Our results showed that an average simulation model can mimic general project growth trends like the number of commits and files well and thus, can help project managers in, e.g., controlling the onboarding of developers. Besides, the simulated co-change evolution could be improved significantly using project-specific data.


2019 ◽  
Vol 6 (Supplement_2) ◽  
pp. S835-S835
Author(s):  
Oguzhan Alagoz ◽  
Elizabeth Scaria ◽  
Anna K Barker ◽  
Nasia Safdar

Abstract Background Visitor contact precautions (VCP) have been suggested to reduce the transmission of Clostridiodes difficile at healthcare institutions. However, there are no data describing the impact of VCP on hospital-acquired C. difficile infection (HO-CDI) rates. Enforcing VCP for CDI control is also controversial, as VCP are poorly implemented and highly variable. Methods We developed an agent-based simulation model of C. difficile transmission at a model 200-bed acute-care adult hospital. Our agent-based simulation model represented interactions among the physicians, nurses, patients, visitors, and physical environment. We used the agent-based simulation model to evaluate the impact of VCP on reducing HO-CDI considering many different hospital settings and various assumptions on patient susceptibility, adherence rates to other infection control practices, interactions between healthcare workers and patients. Results VCP did not reduce the CDC-defined HO-CDI rates by more than 1% in any of the tested scenarios and hospital settings. Increasing the adherence of hand hygiene of healthcare workers to 56% from a baseline estimate of 55%, or compliance to room cleaning to 50% from a baseline estimate of 47% have led to higher rates of reduction in CDI compared with VCP. Conclusion This is the first mathematical model to quantify the reduction in HO-CDI with VCP. The agent-based simulation model suggests that the impact of VCP on hospital-onset CDI is minimal and hospitals can achieve a higher rate of reduction for HO-CDI by implementing other interventions such as healthcare worker hand hygiene, environmental cleaning and healthcare worker contact precautions. Further studies are needed to evaluate the impact of VCP on C. difficile colonization in community. Disclosures All authors: No reported disclosures.


Author(s):  
Oguzhan Alagoz ◽  
Ajay K. Sethi ◽  
Brian W. Patterson ◽  
Matthew Churpek ◽  
Nasia Safdar

ABSTRACTBackgroundAcross the U.S., various social distancing measures were implemented to control COVID-19 pandemic. However, there is uncertainty in the effectiveness of such measures for specific regions with varying population demographics and different levels of adherence to social distancing. The objective of this paper is to determine the impact of social distancing measures in unique regions.MethodsWe developed COVid-19 Agent-based simulation Model (COVAM), an agent-based simulation model (ABM) that represents the social network and interactions among the people in a region considering population demographics, limited testing availability, imported infections from outside of the region, asymptomatic disease transmission, and adherence to social distancing measures. We adopted COVAM to represent COVID-19-associated events in Dane County, Wisconsin, Milwaukee metropolitan area, and New York City (NYC). We used COVAM to evaluate the impact of three different aspects of social distancing: 1) Adherence to social distancing measures; 2) timing of implementing social distancing; and 3) timing of easing social distancing.ResultsWe found that the timing of social distancing and adherence level had a major effect on COVID-19 occurrence. For example, in NYC, implementing social distancing measures on March 5, 2020 instead of March 12, 2020 would have reduced the total number of confirmed cases from 191,984 to 43,968 as of May 30, whereas a 1-week delay in implementing such measures could have increased the number of confirmed cases to 1,299,420. Easing social distancing measures on June 1, 2020 instead of June 15, 2020 in NYC would increase the total number of confirmed cases from 275,587 to 379,858 as of July 31.ConclusionThe timing of implementing social distancing measures, adherence to the measures, and timing of their easing have major effects on the number of COVID-19 cases.Primary Funding SourceNational Institute of Allergy and Infectious Diseases Institute


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