#stochasticmodeling

[jjbrine]

CELESTIAL PANGEA

CELESTIAL PANGEA is in full swing. This transition changes everything. Hell is heaven & heaven is hell & there is no border. It’s like stochastic modeling m for psychic impossibilities that may demonstrate that we are thinking the same thing. Randomness is relative to perspective as with anything. A metaphor means the most to me when Eye take it metomphysically. METOMPHYSICS is a word Eye made up and thus it is now a real word to me. It is the discipline charting the transversing of the physical into the metaphysical and vice-versa. Questions CONTAIN the answer to all things; the activation of understanding. Isn’t that what God is saying when you and me are talking?

[gmmadrid-blog]

PMA - BI Glossary

New Terms

Business Process Modeling

The analytical representation or illustration of an organization’s business processes.        

http://whatis.techtarget.com/definition/business-process-modeling

Process Simulation Modeling (PSIM)  

Process Modeling and Design involves visual models of activities, resources, inputs, outputs, and business rules. The outcome of the as-is process model is a shared understanding of how the current business process works. This reveals information that is otherwise difficult to document and comprehend. As a result of this step, it is not uncommon for process owners, suppliers, and customers to identify process improvement ideas. Process models proposed to-be processes  provide visualizations of future-state alternatives.

http://www.technologymultipliers.com/process-simulation-modeling-and-analysis

 Decision Support Systems (DSS)

A specific class of computerized information system that supports business and organizational decision-making activities.            

https://www.informationbuilders.com/decision-support-systems-dss

 Performance Indicators (KPIs)

A measurable value that demonstrates how effectively a company is achieving key business objectives.  

https://www.klipfolio.com/resources/articles/what-is-a-key-performance-indicator

 AB Testing         

Is comparing two versions of a web page to see which one performs better. You compare two web pages by showing the two variants (let's call them A and B) to similar visitors at the same time.      

https://vwo.com/ab-testing/

 Balanced Scorecards

A management system aimed at translating an organization's strategic goals into a set of performance objectives that, in turn, are measured, monitored and changed if necessary to ensure that the organization's strategic goals are met.

http://searchcio.techtarget.com/definition/balanced-scorecard-methodology

  Stand-Alone Simulation vs Integrated Simulation            

Stand-Alone Simulation agrees with the notion that you train as you learn where Integrated Simulation is based more on experience and observation (experiential learning) used to enrich and support real world systems

Sokolowski J., Banks C. (2012) Real World Applications in Modeling and Simulation, John Wily & Sons, Inc.

 Complicated and Complex Systems        

Complicated and Complex Systems the main difference between complicated and complex systems is that with the former, one can usually predict outcomes by knowing the starting conditions. In a complex system, the same starting conditions can produce different outcomes, depending on interactions of the elements in the system.”

http://www.businessofgovernment.org/article/managing-complicated-vs-complex

  Fidelity and Validity      

Validity generally means how closely the simulated results match the data collected from real life case. Fidelity generally means how closely the simulation replicates the environment, responses, and controls.               

https://www.quora.com/The-difference-between-validity-and-fidelity-in-simulation

 Discrete-Event Simulation (DES)              

The process of codifying the behavior of a complex system as an ordered sequence of well-defined events. In this context, an event comprises a specific change in the system's state at a specific point in time.             

http://whatis.techtarget.com/definition/discrete-event-simulation-DES

  The System Dynamics (SD)         

System Dynamics is a computer-aided approach to policy analysis and design.  It applies to dynamic problems arising in complex social, managerial, economic, or ecological systems–literally any dynamic systems characterized by interdependence, mutual interaction, information feedback, and circular causality.         

http://lm.systemdynamics.org/what-is-s/

  Discrete vs Continuous Simulation Paradigms   

Discrete event simulation is appropriate for systems whose state is discrete and changes at particular time point and then remains in that state for some time. Continuous simulation is appropriate for systems with a continuous state that changes continuously over time.

https://www.researchgate.net/post/what_is_the_exact_difference_between_Continuous_discrete_event_and_discrete_rate_simulation

  Deterministic vs Stochastic Simulation Paradigms

"In deterministic models, the output of the model is fully determined by the parameter values and the initial conditions initial conditions. Stochasticmodels possess some inherent randomness.  The same set of parameter values and initial conditions will lead to an ensemble of   different outputs."

https://www4.stat.ncsu.edu/~gross/BIO560%20webpage/slides/Jan102013.pdf

  Static vs Dynamic Simulation Paradigms

A static model is one which contains no internal history of either input values previously applied, values of internal variables, or output values. The defining feature of a dynamic model is that unlike the static model, it does maintain an internal 'memory' of some combination of prior inputs, internal variables, and outputs.                 

http://www.edscave.com/static-vs.-dynamic-models.html

  Monte Carlo Simulation              

Also known as “probability simulation” is a technique used to understand the impact of risk and uncertainty in financial, project management, cost, and other forecasting models."

https://www.riskamp.com/files/RiskAMP%20-%20Monte%20Carlo%20Simulation.pdf

  Recognition-Primed Decision Model (RPD)         

The RPD Process highlights the three simple steps that we go through, often subconsciously, when we need to make a quick decision. This is based on “pattern recognition,” and on how we can use our past experiences of similar situations to make decisions. The three steps are:  Experiencing the situation, Analyzing the situation, Implementing the decision.

https://www.mindtools.com/blog/corporate/wp-content/uploads/sites/2/2015/03/Recognition-Primed-Decision-Process1.pdf

  Finite State Machine

Online   a computation model that can be implemented with hardware or software and can be used to simulate sequential logic and some computer programs. Finite state automata generate regular languages. Finite state machines can be used to model problems in many fields including mathematics, artificial intelligence, games, and linguistics.         

https://brilliant.org/wiki/finite-state-machines/

  Neural Networks            

An information processing paradigm that is inspired by the way biological nervous systems, such as the brain, process information. The key element of this paradigm is the novel structure of the information processing system. It is composed of a large number of highly interconnected processing elements (neurones) working in unison to solve specific problems.

https://www.doc.ic.ac.uk/~nd/surprise_96/journal/vol4/cs11/report.html#What is a Neural Network

 Fuzzy Logic and Fuzzy Inference

Fuzzy inference is the process of formulating the mapping from a given input to an output using fuzzy logic. The mapping then provides a basis from which decisions can be made, or patterns discerned.  Fuzzy logic is an approach to computing based on "degrees of truth" rather than the usual "true or false" (1 or 0) Boolean logic on which the modern computer is based.

http://whatis.techtarget.com/definition/fuzzy-logic

https://www.mathworks.com/help/fuzzy/fuzzy-inference-process.html?requestedDomain=true

  Agent-Based Modeling

In agent-based modeling (ABM), a system is modeled as a collection of autonomous decision-making entities called agents. Each agent individually assesses its situation and makes decisions on the basis of a set of rules. Agents may execute various behaviors appropriate for the system they represent—for example, producing, consuming, or selling. Repetitive competitive interactions between agents are a feature of agent-based modeling, which relies on the power of computers to explore dynamics out of the reach of pure mathematical methods (1, 2).

http://www.pnas.org/content/99/suppl_3/7280

  Object-Oriented Programming

Object-oriented programming (OOP) is a programming language model organized around objects rather than "actions" and data rather than logic. Historically, a program has been viewed as a logical procedure that takes input data, processes it, and produces output data.         

http://searchmicroservices.techtarget.com/definition/object-oriented-programming-OOP

[jjbrine]

#CELESTIALPANGEA is in full swing. This transition changes everything. Hell is heaven & heaven is hell & there is no border. It's like #stochasticmodeling for psychic impossibilities that may demonstrate that we are thinking the same thing. Randomness is relative to perspective as with anything. A metaphor means the most to me when Eye take it metomphysically. #METOMPHYSICS is a word Eye made up and thus it is now a #realword to me. It is the discipline charting the transversing of the physical into the metaphysical and vice-versa. Questions CONTAIN the answer to all things; the activation of understanding. Isn't that what God is saying when you and me are talking? (at Istanbul, Türkiye)