Qualitative simulation of organization quality specific immune decision-making of manufacturing enterprises based on QSIM algorithm simulation

2021 ◽  
pp. 1-18
Author(s):  
Qiang Liu ◽  
Xiaoli Qu ◽  
Danyu Zhao ◽  
Yu Guo
Keyword(s):  
Decision Making ◽  
Simulation Method ◽  
Engineering Management ◽  
Decision Variable ◽  
Science And Engineering ◽  
Qualitative Simulation ◽  
Manufacturing Enterprises ◽  
Decision Variables ◽  
Organization Quality ◽  
Simulation Results

Quality is the core of the enterprise, strengthening organization quality specific immune is the key channel. Organization quality specific immune belongs to science and engineering management field, QSIM qualitative simulation method that refer to computational simulation algorithm is widely used in the science and engineering management field, QSIM qualitative simulation method can solve science and engineering management issues effectively. In this study, qualitative simulation QSIM theory is used to analyze and reason the organization quality specific immune decision of manufacturing enterprises. Combined with the pressure-state-response framework, the management mechanism of organization quality specific immune is analyzed according to state variables, decision variables, system variables and environment variables, and further the qualitative simulation rules for organization quality specific immune decision-making are set according to the causal relationships among variables of organization quality specific immune. This study sets organization quality monitor, organization quality defense and organization quality memory as the decision variables, uses QSIM algorithm for simulating organization quality specific immune decision-making reasoning, compares with the influences of single decision variable and multi-decision variables on organization quality specific immune system through simulation results. Simulation results indicate that QSIM algorithm simulation can be used to simulate and reason organization quality specific immune decision-making in order to help manufacturing enterprises reasonably enhance organization quality specific immune performance and quality performance through three decision variables of organization quality monitor, organization quality defense and organization quality memory. The simulation results will provide new revelation for organization quality specific immune decision-making of manufacturing enterprises.

scholarly journals Strategy-dependent effects of working-memory limitations on human perceptual decision-making

2021 ◽  
Author(s):  
Kyra Schapiro ◽  
Kresimir Josic ◽  
Zachary Kilpatrick ◽  
Joshua I Gold
Keyword(s):  
Decision Making ◽  
Working Memory ◽  
Decision Variable ◽  
Perceptual Decision Making ◽  
Perceptual Decision ◽  
Human Psychophysics ◽  
Decision Variables ◽  
The Impact ◽  
The Brain ◽  
Over Time

Deliberative decisions based on an accumulation of evidence over time depend on working memory, and working memory has limitations, but how these limitations affect deliberative decision-making is not understood. We used human psychophysics to assess the impact of working-memory limitations on the fidelity of a continuous decision variable. Participants decided the average location of multiple visual targets. This computed, continuous decision variable degraded with time and capacity in a manner that depended critically on the strategy used to form the decision variable. This dependence reflected whether the decision variable was computed either: 1) immediately upon observing the evidence, and thus stored as a single value in memory; or 2) at the time of the report, and thus stored as multiple values in memory. These results provide important constraints on how the brain computes and maintains temporally dynamic decision variables.

scholarly journals Evidence and urgency related EEG signals during dynamic decision-making in humans

2020 ◽  
Author(s):  
Y. Yau ◽  
T. Hinault ◽  
M. Taylor ◽  
P. Cisek ◽  
L.K. Fellows ◽  
...  
Keyword(s):  
Decision Making ◽  
Dynamic Decision Making ◽  
Decision Variable ◽  
Decision Threshold ◽  
Neural Signals ◽  
Addictive Disorders ◽  
Evidence Accumulation ◽  
Gating Model ◽  
Decision Variables ◽  
Sensory Evidence

AbstractA successful class of models link decision-making to brain signals by assuming that evidence accumulates to a decision threshold. These evidence accumulation models have identified neuronal activity that appears to reflect sensory evidence and decision variables that drive behavior. More recently, an additional evidence-independent and time-variant signal, named urgency, has been hypothesized to accelerate decisions in the face of insufficient evidence. However, most decision-making paradigms tested with fMRI or EEG in humans have not been designed to disentangle evidence accumulation from urgency. Here we use a face-morphing decision-making task in combination with EEG and a hierarchical Bayesian model to identify neural signals related to sensory and decision variables, and to test the urgency-gating model. We find that an evoked potential time-locked to the decision, the centroparietal positivity, reflects the decision variable from the computational model. We further show that the unfolding of this signal throughout the decision process best reflects the product of sensory evidence and an evidence-independent urgency signal. Urgency varied across subjects, suggesting that it may represent an individual trait. Our results show that it is possible to use EEG to distinguish neural signals related to sensory evidence accumulation, decision variables, and urgency. These mechanisms expose principles of cognitive function in general and may have applications to the study of pathological decision-making as in impulse control and addictive disorders.Significance StatementPerceptual decisions are often described by a class of models that assumes sensory evidence accumulates gradually over time until a decision threshold is reached. In the present study, we demonstrate that an additional urgency signal impacts how decisions are formed. This endogenous signal encourages one to respond as time elapses. We found that neural decision signals measured by EEG reflect the product of sensory evidence and an evidence-independent urgency signal. A nuanced understanding of human decisions, and the neural mechanisms that support it, can improve decision-making in many situations and potentially ameliorate dysfunction when it has gone awry.

scholarly journals Limitations of a proposed correction for slow drifts in decision criterion

2021 ◽  
Author(s):  
Diksha Gupta ◽  
Carlos D Brody
Keyword(s):  
Decision Making ◽  
Simulated Data ◽  
Decision Criterion ◽  
Decision Variable ◽  
Generative Process ◽  
Latent Trajectory ◽  
Heuristic Strategies ◽  
Decision Variables ◽  
Wide Range ◽  
Trial History

Trial history biases in decision-making tasks are thought to reflect systematic updates of decision variables, therefore their precise nature informs conclusions about underlying heuristic strategies and learning processes. However, random drifts in decision variables can corrupt this inference by mimicking the signatures of systematic updates. Hence, identifying the trial-by-trial evolution of decision variables requires methods that can robustly account for such drifts. Recent studies (Lak 20, Mendonça 20) have made important advances in this direction, by proposing a convenient method to correct for the influence of slow drifts in decision criterion, a key decision variable. Here we apply this correction to a variety of updating scenarios, and evaluate its performance. We show that the correction fails for a wide range of commonly assumed systematic updating strategies, distorting one's inference away from the veridical strategies towards a narrow subset. To address these limitations, we propose a model-based approach for disambiguating systematic updates from random drifts, and demonstrate its success on real and synthetic datasets. We show that this approach accurately recovers the latent trajectory of drifts in decision criterion as well as the generative systematic updates from simulated data. Our results offer recommendations for methods to account for the interactions between history biases and slow drifts, and highlight the advantages of incorporating assumptions about the generative process directly into models of decision-making.

scholarly journals Evaluation and Decision Making of Organization Quality Specific Immunity Based on MGDM-IPLAO Method

Open Physics ◽  
2019 ◽  
Vol 17 (1) ◽  
pp. 863-870
Author(s):  
Qiang Liu ◽  
Hui-Ya Hu ◽  
Yu Guo ◽  
Fei-Xue Yang
Keyword(s):  
Decision Making ◽  
Quality Management ◽  
Empirical Analysis ◽  
Group Decision Making ◽  
Group Decision ◽  
Aggregation Operators ◽  
Manufacturing Enterprises ◽  
Specific Immunity ◽  
Starting Point ◽  
Organization Quality

Abstract As the starting point, the immunity theory is introduced into the organization quality management, combined with the organization quality specific immunity system, the evaluation index system of organization quality specific immunity is designed. And the evaluation and multi-attribute group decision making model of organization quality specific immunity based on the immunity perspective is constructed by the method of multi-attribute group decision making of intuitive pure linguistic aggregation operators, empirical analysis is carried out by the research objects of relevant experts, representative and typical manufacturing enterprises, the empirical analysis results indicate that multi-attribute group decision making method of intuitive pure linguistic aggregation operators can choose and determine the optimization evaluation solution and the best decision making of partners, confirm the highest value over all partners for organization quality specific immunity system, the method of multi-attribute group decision making of intuitive pure linguistic aggregation operators has validity, feasibility and operability in evaluation and decision making of organization quality specific immunity. Empirical analysis results and conclusion have certain practical value, which provide new ideas to solve the problem of multi-attribute decision making of intuitive information mixed with pure linguistic information, and provides the basis for the effective selection of the best partners for manufacturing enterprises of the supply chain from the perspective of quality management.

Qualitative simulation and related approaches for the analysis of dynamic systems

2004 ◽  
Vol 19 (2) ◽  
pp. 93-132 ◽  
Author(s):  
HIDDE DE JONG
Keyword(s):  
Qualitative Analysis ◽  
Dynamic Systems ◽  
Quantitative Information ◽  
Simulation Methods ◽  
Science And Engineering ◽  
Computational Framework ◽  
Combinatorial Explosion ◽  
Qualitative Simulation ◽  
Qualitative Phase ◽  
Made In

Methods for qualitative simulation allow predictions on the dynamics of a system to be made in the absence of quantitative information, by inferring the range of possible qualitative behaviors compatible with the structure of the system. This article reviews QSIM and other qualitative simulation methods. It discusses two problems that have seriously compromised the application of these methods to realistic problems in science and engineering: the occurrence of spurious behavior predictions and the combinatorial explosion of the number of behavior predictions. In response to these problems, related approaches for the qualitative analysis of dynamic systems have emerged: qualitative phase-space analysis and semi-quantitative simulation. The article argues for a synthesis of these approaches in order to obtain a computational framework for the qualitative analysis of dynamic systems. This should provide a solid basis for further upscaling and for the development of model-based reasoning applications of a wider scope.

A partner selection problem for complex product of manufacturing enterprises in supply chain

2021 ◽  
pp. 1-13
Author(s):  
Congdong Li ◽  
Yinyun Yu ◽  
Wei Xu ◽  
Jianzhu Sun
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Fuzzy Theory ◽  
Partner Selection ◽  
Manufacturing Companies ◽  
Complex Product ◽  
Manufacturing Enterprises ◽  
Collaborative Manufacturing ◽  
Matching Degree ◽  
Decision Making Model

In order to better meet customer needs and respond to market demands more quickly, mounting number of manufacturing companies have begun to bid farewell to the traditional unitary manufacturing model. The collaborative manufacturing model has become a widely adopted manufacturing model for manufacturing companies. Aiming at the problem of partner selection for collaborative manufacturing of complex products in a collaborative supply chain environment, this paper proposes a multi-objective decision-making model that comprehensively considers the maximization of the matching degree of manufacturing capacity and the profits of supply chain, and gives the modeling process and application steps in detail. The method first uses fuzzy theory to evaluate the manufacturing capabilities of candidate collaborative manufacturing partners. Secondly, Vector Space Model (VSM) is used to calculate the matching degree of manufacturing capacity and manufacturing demand. Then, the paper studied the profit of the supply chain under the “non-cooperative” mechanism and the “revenue sharing” mechanism. Furthermore, the decision-making model is established. Finally, a simulation was carried out by taking complex product manufacturing of Gree enterprise as an example. The research results show the feasibility and effectiveness of the method.

Study of HVDC System and Subsynchronous Oscillation

2015 ◽  
Vol 1092-1093 ◽  
pp. 356-361
Author(s):  
Peng Fei Zhang ◽  
Lian Guang Liu
Keyword(s):  
Power Plant ◽  
Time Domain ◽  
Simulation Method ◽  
Time Domain Simulation ◽  
Stable Convergence ◽  
Turbine Generator ◽  
Plant Model ◽  
Subsynchronous Oscillation ◽  
Hvdc System ◽  
Simulation Results

With the application and development of Power Electronics, HVDC is applied more widely China. However, HVDC system has the possibilities to cause subsynchronous torsional vibration interaction with turbine generator shaft mechanical system. This paper simply introduces the mechanism, analytical methods and suppression measures of subsynchronous oscillation. Then it establishes a power plant model in islanding model using PSCAD, and analyzes the effects of the number and output of generators to SSO, and verifies the effect of SEDC and SSDC using time-domain simulation method. Simulation results show that the more number and output of generators is detrimental to the stable convergence of subsynchronous oscillation, and SEDC、SSDC can restrain unstable SSO, avoid divergence of SSO, ensure the generators and system operate safely and stably

scholarly journals GBUO: “The Good, the Bad, and the Ugly” Optimizer

2021 ◽  
Vol 11 (5) ◽  
pp. 2042
Author(s):  
Hadi Givi ◽  
Mohammad Dehghani ◽  
Zeinab Montazeri ◽  
Ruben Morales-Menendez ◽  
Ricardo A. Ramirez-Mendoza ◽  
...  
Keyword(s):  
High Dimension ◽  
Essential Role ◽  
Optimization Problems ◽  
Optimization Algorithms ◽  
Stochastic Search ◽  
Objective Functions ◽  
Science And Engineering ◽  
Fixed Dimension ◽  
Dimension Functions ◽  
Simulation Results

Optimization problems in various fields of science and engineering should be solved using appropriate methods. Stochastic search-based optimization algorithms are a widely used approach for solving optimization problems. In this paper, a new optimization algorithm called “the good, the bad, and the ugly” optimizer (GBUO) is introduced, based on the effect of three members of the population on the population updates. In the proposed GBUO, the algorithm population moves towards the good member and avoids the bad member. In the proposed algorithm, a new member called ugly member is also introduced, which plays an essential role in updating the population. In a challenging move, the ugly member leads the population to situations contrary to society’s movement. GBUO is mathematically modeled, and its equations are presented. GBUO is implemented on a set of twenty-three standard objective functions to evaluate the proposed optimizer’s performance for solving optimization problems. The mentioned standard objective functions can be classified into three groups: unimodal, multimodal with high-dimension, and multimodal with fixed dimension functions. There was a further analysis carried-out for eight well-known optimization algorithms. The simulation results show that the proposed algorithm has a good performance in solving different optimization problems models and is superior to the mentioned optimization algorithms.

A Reformative Simulation Method of Motor Pole Core Vibration Characteristics

2013 ◽  
Vol 331 ◽  
pp. 118-123
Author(s):  
Tian Hui Ding ◽  
Yun Hua Chen ◽  
Lei Tian
Keyword(s):  
Reference Value ◽  
Simulation Method ◽  
Vibration Characteristics ◽  
New Method ◽  
Motor Design ◽  
Simulation Results ◽  
Vibration Performance

As to directing motor design, it is very important to make sure that the motor’s forecast of vibration performance has reference value. So, it must need motor’s parts vibration characteristics simulation results are so close to their characteristics. This paper puts forward a new simulation method of motor pole core vibration characteristics, this method includes setting anisotropy material attributes multipartite, getting attributes parameters values which are based on recommended fitting curves, modeling and equating windings, equating dipping lacquer and so on. Combining with experiments, the new method is validated its availability.

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