An automated efficiency model (AEM) is a mathematical model that estimates a real estate property’s efficiency by using details specific to the property which are available publicly and/or housing characteristics which are aggregated over a given area such as a zip code. AEMs have some similarities to an automated valuation model (AVM) in terms of concept, advantages and disadvantages. AEMs calculate specific efficiencies such as location, water, energy or solar efficiency. The Council of Multiple Listing Services defines an AEM as, “any algorithm or scoring model that estimates the [efficiency] of a home without an on-site inspection. They are similar to Automated Valuation Models (AVMs), but are more reliant on public data such as square footage...and estimated energy usage.” Most AEMs calculate a property’s selected efficiency by analyzing available public information and may also apply proprietary data or formulas, and allow for a user such as a home owner to make additional inputs. Housing characteristics such as age of the home or square footage may be obtained by data providers such as those on this list of online real estate databases or a similar offerings. Estimates of energy usage may be available from published sources such as through the Residential Energy Consumption Survey by the Energy Information Administration. (Wikipedia).
If you are interested in learning more about this topic, please visit http://www.gcflearnfree.org/ to view the entire tutorial on our website. It includes instructional text, informational graphics, examples, and even interactives for you to practice and apply what you've learned.
From playlist Automation
AI for Engineers: Building an AI System
Artificial intelligence (AI) is a simulation of intelligent human behavior. It is designed to perceive its environment, make decisions, and take action. Get an overview of AI for engineers, and discover the ways in which artificial intelligence fits into an engineering workflow. You’ll lea
From playlist 深度学习(Deep Learning)
The Benefits of Functional Architectures | Systems Engineering, Part 3
See the other videos in this series: https://www.youtube.com/playlist?list=PLn8PRpmsu08owzDpgnQr7vo2O-FUQm_fL Functional, logical, and physical architectures are important tools for designing complex systems. We describe what architectures are and how they contribute to the early stages of
From playlist Systems Engineering
Design and Deployment of an Automated Parking Valet on ROS and ROS2 Networks
The development of an autonomous system requires an increase in the number of sensors and actuators to perceive its environment and control every element in the system dexterously. The challenge is to control autonomous systems to ensure their safety results in more diverse components and
From playlist Tips and Tricks from MATLAB and Simulink Developers
Benjamin Seibold: "Energy Impact of Automated Vehicles used as Sparse Traffic Controllers"
Mathematical Challenges and Opportunities for Autonomous Vehicles 2020 Workshop II: Safe Operation of Connected and Autonomous Vehicle Fleets "Energy Impact of Automated Vehicles used as Sparse Traffic Controllers" Benjamin Seibold - Temple University, Mathematics Abstract: It is a popul
From playlist Mathematical Challenges and Opportunities for Autonomous Vehicles 2020
Michael Hyland: "Integrating State-of-the-Art Mobility-on-Demand Fleet Models into Transportatio..."
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From playlist Mathematical Challenges and Opportunities for Autonomous Vehicles 2020
Webinar: How can firms create a strategic advantage by integrating processes
Banks across the globe have made tremendous strides in enhancing their forecasting capability related to balance sheet and PnL, which were generally developed in response to regulatory requirements. Banks with more mature processes are now focusing on how these models and other tools can l
From playlist Webinars: At home with the experts
Devops Tutorial For Beginners [ 🔥 Updated] | Introduction To DevOps | DevOps Training |Simplilearn
🔥DevOps Engineer Master Program (Discount Code: YTBE15): https://www.simplilearn.com/devops-engineer-masters-program-certification-training?utm_campaign=DevOpsTutorialForBeginnersOct19-OJecuyYgcA4&utm_medium=DescriptionFF&utm_source=youtube 🔥Post Graduate Program In DevOps: https://www.si
From playlist DevOps Tutorial For Beginners 🔥 | Simplilearn [Updated]
Dan Work: "Transportation Engineering for Connected and Automated Vehicles" (Part 2/2)
Watch part 1/2 here: https://youtu.be/nQBTMTZoBhU Mathematical Challenges and Opportunities for Autonomous Vehicles Tutorials 2020 "Transportation Engineering for Connected and Automated Vehicles" (Part 2/2) Dan Work - Vanderbilt University Institute for Pure and Applied Mathematics, UC
From playlist Mathematical Challenges and Opportunities for Autonomous Vehicles 2020
Ross King: "Automating Science using Robot Scientists"
Machine Learning for Physics and the Physics of Learning 2019 Workshop I: From Passive to Active: Generative and Reinforcement Learning with Physics "Automating Science using Robot Scientists" Ross King, University of Manchester Institute of Science and Technology (UMIST) Abstract: A Rob
From playlist Machine Learning for Physics and the Physics of Learning 2019
2014 JUC SF - Jenkins: Enabling Agility and Efficiency
By, Laxmikant Sharma eBay and PayPal have been using Jenkins (and previously Hudson) for a very long time. Right from provisioning CI VMs via Mesos/Dockers, securing CI, pipelines for code propagation etc., Jenkins has enabled us to execute brilliantly on every single aspect of PDLC. In fa
From playlist Jenkins User Conference San Francisco 2014
Balavijayan Ganesan interviewed at TOC 2011
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From playlist TOC 2011
What If We Automated Construction?
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From playlist Offsite Construction - The B1M
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Help us to make future videos for you. Make LE's efforts sustainable. Please support us at Patreon.com ! https://www.patreon.com/LearnEngineering The operation of an automatic transmission is explained here with help of animation. Allison-1000 transmission model, which has 6 speed and r
From playlist Automobile Engineering
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From playlist Data-driven Physical Simulations (DDPS) Seminar Series