Exposing System and Model Disparity and Agreement Using Wavelets

2018 ◽  
Vol 3 (2) ◽  
Author(s):  
Andrew D. Atkinson ◽  
Raymond R. Hill ◽  
Joseph J. Pignatiello ◽  
G. Geoffrey Vining ◽  
Edward D. White ◽  
...  
Keyword(s):  
Development Process ◽  
Model Development ◽  
Model Verification ◽  
Verification And Validation ◽  
High Dimensional ◽  
Model Data ◽  
Accurate Representation ◽  
Model Verification And Validation ◽  
Model Development Process ◽  
Functional Output

Model verification and validation (V&V) remain a critical step in the simulation model development process. A model requires verification to ensure that it has been correctly transitioned from a conceptual form to a computerized form. A model also requires validation to substantiate the accurate representation of the system it is meant to simulate. Validation assessments are complex when the system and model both generate high-dimensional functional output. To handle this complexity, this paper reviews several wavelet-based approaches for assessing models of this type and introduces a new concept for highlighting the areas of contrast and congruity between system and model data. This concept identifies individual wavelet coefficients that correspond to the areas of discrepancy between the system and model.

scholarly journals A Survey of Domain Knowledge Elicitation in Applied Machine Learning

2021 ◽  
Vol 5 (12) ◽  
pp. 73
Author(s):  
Daniel Kerrigan ◽  
Jessica Hullman ◽  
Enrico Bertini
Keyword(s):  
Machine Learning ◽  
Domain Knowledge ◽  
Development Process ◽  
Model Development ◽  
Knowledge Elicitation ◽  
Future Directions ◽  
Domain Experts ◽  
Applied Machine Learning ◽  
Elicitation Process ◽  
Model Development Process

Eliciting knowledge from domain experts can play an important role throughout the machine learning process, from correctly specifying the task to evaluating model results. However, knowledge elicitation is also fraught with challenges. In this work, we consider why and how machine learning researchers elicit knowledge from experts in the model development process. We develop a taxonomy to characterize elicitation approaches according to the elicitation goal, elicitation target, elicitation process, and use of elicited knowledge. We analyze the elicitation trends observed in 28 papers with this taxonomy and identify opportunities for adding rigor to these elicitation approaches. We suggest future directions for research in elicitation for machine learning by highlighting avenues for further exploration and drawing on what we can learn from elicitation research in other fields.

scholarly journals Strategic Business Model Development in Ecosystems

2021 ◽  
Author(s):  
◽  
Dominik Mann
Keyword(s):  
Business Model ◽  
Development Process ◽  
Business Models ◽  
Model Development ◽  
Entrepreneurial Ventures ◽  
And Performance ◽  
Integration Strategies ◽  
Model Components ◽  
Business Model Development ◽  
Model Development Process

<p>Designing and strategically developing viable business models is vital for value creation and capture and in turn for the survival and performance of entrepreneurial ventures. However, the widely held firm-centric and static business model perspective appears inadequate to reflect the realities of increasingly blurred industry boundaries, interconnected economies, and the resulting collapse of incumbent value chains. This PhD thesis adds understanding of the dynamic business model development process from an ecosystem perspective. The evolution of ten entrepreneurial ventures’ business models was documented and investigated through longitudinal in-depth case studies over twelve months. Analysing and comparing the cases revealed strategies that resulted in the development of effective interactive structures and robust value co-creation and capture mechanisms. The development of interactive structures, i.e. firm-ecosystem fits, was either supported by a focused or diversified ecosystem integration approach underpinned by heterogeneous interdependencies of value proposition and business model components across ecosystems. The obtained insights allowed the derivation of sets of capabilities that supported the business model development process and enhanced entrepreneurial ventures’ chances of survival. The findings have several implications for advancements of the business model theory. In particular they indicate what integration strategies can inform entrepreneurs’ and managers’ business model design and execution strategies for operating in increasingly complex ecosystems.</p>

scholarly journals Load Model Verification, Validation and Calibration Framework by Statistical Analysis on Field Data

2017 ◽  
Vol 18 (6) ◽  
Author(s):  
Xiangqing Jiao ◽  
Yuan Liao ◽  
Thai Nguyen
Keyword(s):  
Statistical Analysis ◽  
System Analysis ◽  
Research Work ◽  
Field Measurements ◽  
Model Verification ◽  
Verification And Validation ◽  
Load Model ◽  
Load Models ◽  
Utility System ◽  
Model Verification And Validation

AbstractAccurate load models are critical for power system analysis and operation. A large amount of research work has been done on load modeling. Most of the existing research focuses on developing load models, while little has been done on developing formal load model verification and validation (V&V) methodologies or procedures. Most of the existing load model validation is based on qualitative rather than quantitative analysis. In addition, not all aspects of model V&V problem have been addressed by the existing approaches. To complement the existing methods, this paper proposes a novel load model verification and validation framework that can systematically and more comprehensively examine load model’s effectiveness and accuracy. Statistical analysis, instead of visual check, quantifies the load model’s accuracy, and provides a confidence level of the developed load model for model users. The analysis results can also be used to calibrate load models. The proposed framework can be used as a guidance to systematically examine load models for utility engineers and researchers. The proposed method is demonstrated through analysis of field measurements collected from a utility system.

Design of the Engineering-Oriented Equipment Requirement Demonstration Model Base

2014 ◽  
Vol 513-517 ◽  
pp. 3612-3616
Author(s):  
Yan Ping Fan ◽  
Qi Sheng Guo ◽  
Jie Bai ◽  
Jin Liang Wang
Keyword(s):  
Design Pattern ◽  
Development Process ◽  
Model Development ◽  
Model Management ◽  
Model Base ◽  
Model Driven ◽  
Management Technology ◽  
Application Requirements ◽  
Model Development Process

Aiming at the engineering-oriented application requirements of the equipment requirement demonstration, the demonstration process driven by models is regarded as the essential goal. Firstly, the activities and the modeling requirements of the equipment requirement demonstration are analyzed in detail. Thereafter, the model system of the equipment requirement demonstration is built. Focusing on the design of the model base, the model-driven model development process and the design pattern of the models based on MVC are put forward and discussed emphatically. The VV&A mechanism is designed to improve the quality of the models. According to the management requirements of the model base, the model management technology based on ontology is put forward, and then the run mechanism of the model base is studied. Throughout all these designs, the models simulating the equipment requirement demonstration activities can be understood and reused better, and can satisfy the elementary requirements building the toolkits based on these models. Simultaneity, the equipment requirement demonstration activities can be regulated and formalized with the toolkits.

A Wavelet Synthesis Technique for Creating Realistic Virtual Environment Sounds

2002 ◽  
Vol 11 (5) ◽  
pp. 493-507 ◽  
Author(s):  
Nadine E. Miner ◽  
Thomas P. Caudell
Keyword(s):  
Virtual Environments ◽  
Virtual Environment ◽  
Development Process ◽  
Model Development ◽  
Sound Synthesis ◽  
Model Parameters ◽  
Experiment Validation ◽  
Environment Simulation ◽  
A New Technique ◽  
Model Development Process

This paper describes a new technique for synthesizing realistic sounds for virtual environments. The four-phase technique described uses wavelet analysis to create a sound model. Parameters are extracted from the model to provide dynamic sound synthesis control from a virtual environment simulation. Sounds can be synthesized in real time using the fast inverse wavelet transform. Perceptual experiment validation is an integral part of the model development process. This paper describes the four-phase process for creating the parameterized sound models. Several developed models and perceptual experiments for validating the sound synthesis veracity are described. The developed models and results demonstrate proof of the concept and illustrate the potential of this approach.

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