Complex adaptive system theory,agent-based modeling,and simulation in dominant technology formation

Dominant technology formation is the key for the hightech industry to“cross the chasm”and gain an established foothold in the market(and hence disrupt the regime).Therefore,a stimulus-response model is proposed to investigate the dominant technology by exploring its formation process and mechanism.Specifically,based on complex adaptive system theory and the basic stimulus-response model,we use a combination of agent-based modeling and system dynamics modeling to capture the interactions between dominant technology and the socio-technical landscape.The results indicate the following:(i)The dynamic interaction is“stimulus-reaction-selection”,which promotes the dominant technology’s formation.(ii)The dominant technology’s formation can be described as a dynamic process in which the adaptation intensity of technology standards increases continuously until it becomes the leading technology under the dual action of internal and external mechanisms.(iii)The dominant technology’s formation in the high-tech industry is influenced by learning ability,the number of adopting users and adaptability.Therein,a“critical scale”of learning ability exists to promote the formation of leading technology:a large number of adopting users can promote the dominant technology’s formation by influencing the adaptive response of technology standards to the socio-technical landscape and the choice of technology standards by the socio-technical landscape.There is a minimum threshold and a maximum threshold for the role of adaptability in the dominant technology’s formation.(iv)The socio-technical landscape can promote the leading technology’s shaping in the high-tech industry,and different elements have different effects.This study promotes research on the formation mechanism of dominant technology in the high-tech industry,presents new perspectives and methods for researchers,and provides essential enlightenment for managers to formulate technology strategies.

The Dynamic System Theory of Legal Protection for Personal Information Rights Infringement

The advent of the big data era has presented unprecedented challenges to remedies for personal information infringement in areas such as damage assessment,proof of causation,determination of illegality,fault assessment,and liability.Traditional tort law is unable to provide a robust response for these challenges,which severely hinders human rights protection in the digital society.The dynamic system theory represents a third path between fixed constitutive elements and general clauses.It both overcomes the rigidity of the“allor-nothing”legal effect evaluation mechanism of the“element-effect”model and avoids the uncertainty of the general clause model.It can effectively enhance the flexibility of the legal system in responding to social changes.In light of this,it is necessary to construct a dynamic foundational evaluation framework for personal information infringement under the guidance of the dynamic system theory.By relying on the dynamic interplay effect of various foundational evaluation elements,this framework can achieve a flexible evaluation of the constitutive elements of liability and the legal effects of liability for personal information infringement.Through this approach,the crisis of personal information infringement in the era of big data can be mitigated,and the realization of personal information rights as digital human rights can be promoted.

A Comparison of New General System Theory Philosophy With Einstein and Bohr

The New General System theory was developed to be a theory of everything for complex systems within the world we can observe.This theory was constructed by supplementing a new mind-ether ontology into Bertalanffy’s general system theory framework.This theory is basically a generalization of classical mechanics rather than a revolution to it taken both by Einstein and Bohr in developing their relativity theory and quantum mechanics.The purpose of this paper is to reveal the reasons why Einstein and many others fail to unify relativity theory with quantum mechanics through comparing the main differences in philosophical opinions among NGST,Einstein,and Bohr.It is the hope of the authors that this clarification could speed up the unification process.

APPLICATION OF GREY SYSTEM THEORY TO PROCESSING OF MEASURING DATA IN REVERSE ENGINEERING

The processing of measuri ng data plays an important role in reverse engineering. Based on grey system the ory, we first propose some methods to the processing of measuring data in revers e engineering. The measured data usually have some abnormalities. When the abnor mal data are eliminated by filtering, blanks are created. The grey generation an d GM(1,1) are used to create new data for these blanks. For the uneven data sequ en ce created by measuring error, the mean generation is used to smooth it and then the stepwise and smooth generations are used to improve the data sequence.

Study on the Yield Prediction Model of Processing Tomato Based on the Grey System Theory

[Objective] The research aimed to study the yield prediction model of processing tomato based on the grey system theory.[Method] The variation trend of processing tomato yield was studied by using the grey system theory,and GM（1,1）grey model of processing tomato yield prediction was established.The processing tomato yield in Xinjiang during 2001-2009 was as the example to carry out the instance analysis.[Result] The model had the high forecast accuracy and strong generalization ability,and was reliable for the prediction of recent processing tomato yield.[Conclusion] The research provided the reference for the macro-control of tomato industry,the processing and storage of tomato in Xinjiang.

Controlled-source electromagnetic data processing based on gray system theory and robust estimation

We propose a novel method that combines gray system theory and robust M-estimation method to suppress the interference in controlled-source electromagnetic data. We estimate the standard deviation of the data using a gray model because of the weak dependence of the gray system on data distribution and size. We combine the proposed and threshold method to identify and eliminate outliers. Robust M-estimation is applied to suppress the effect of the outliers and improve the accuracy. We treat the M-estimators of the preserved data as the true data. We use our method to reject the outliers in simulated signals containing noise to verify the feasibility of our proposed method. The processed values are observed to be approximate to the expected values with high accuracy. The maximum relative error is 3.6676%, whereas the minimum is 0.0251%. In processing field data, we observe that the proposed method eliminates outliers, minimizes the root-mean-square error, and improves the reliability of controlled-source electromagnetic data in follow-up processing and interpretation.

Forecasting Model of Coal Requirement Quantity Based on Grey System Theory

The generally used methods of forecasting coal requirement quantity include the analogy method, the outside push method and the cause effect analysis method. However, the precision of forecasting results using these methods is lower. This paper uses the grey system theory, and sets up grey forecasting model GM (1, 3) to coal requirement quantity. The forecasting result for the Chinese coal requirement quantity coincides with the actual values, and this shows that the model is reliable. Finally, this model are used to forecast Chinese coal requirement quantity in the future ten years.

Investigation of the Interactive,Intimidating Relation Between Urbanization and the Environment in an Arid Area Based on Grey System Theory

Taking the Hexi Corridor in western China as an example, this paper studies the interactive intimate i relation between urbanization and the environment in add areas based on the grey system theory. The results show that the grey relational degree between urbanization and the environment is low in the agriculture-oriented cities, modest in the tourism-oriented cities and great in the industry-oriented cities. The changing trend of coupling degree between urbanization and the environment does not entirely agree with that of urbanization or the environment. It showed fluctuating trends, which reflects the compactness and properties of the different stages of the coupling states between urbanization and the environment. In order to achieve a harmonious development with the environment in add areas, traditional development ideas about urbanization should be revised and more attention should be paid to the effect of restriction of water resources and the ecological environment on the development of the economy and society.

Predicting changes in Bitcoin price using grey system theory

Bitcoin is currently the leading global provider of cryptocurrency.Cryptocurrency allows users to safely and anonymously use the Internet to perform digital currency transfers and storage.In recent years,the Bitcoin network has attracted investors,businesses,and corporations while facilitating services and product deals.Moreover,Bitcoin has made itself the dominant source of decentralized cryptocurrency.While considerable research has been done concerning Bitcoin network analysis,limited research has been conducted on predicting the Bitcoin price.The purpose of this study is to predict the price of Bitcoin and changes therein using the grey system theory.The first order grey model(GM(1,1))is used for this purpose.It uses a firstorder differential equation to model the trend of time series.The results show that the GM(1,1)model predicts Bitcoin’s price accurately and that one can earn a maximum profit confidence level of approximately 98%by choosing the appropriate time frame and by managing investment assets.

On the Philosophical Ontology for a General System Theory

System is a very general concept and theoretically speaking, every problem encountered can be modeled as a system. Thus, the general system theory (GST) proposed by Bertalanffy (1968) and developed by many others e.g. Bunge (1977;1979;1983a;1983b) and Maturana and Varela (1980;1987) could be treated as a theory of everything (TOE). However, it is well-known that the present version of GST has not reached the level of TOE because it lacks a clear ontology. Currently, quantum mechanics (QM), Newtonian mechanics (NM) and general relativity (GR), suitable for microscopic, macroscopic and cosmic phenomena respectively are based on very different ontologies. In this paper, a unified ontology for the general system theory which could be applied to any scale from micro to cosmic is proposed. It is expected that this could lay a foundation to generalize GST to TOE.

Optimization approach hydroforming car beam billets based grey system theory

Perfect combination of structural size parameters of the hydroforming billets is essential to obtain even wall thicknesses of the car beam. Finite element （ FE ） analysis on hydroforming car beam was carried out, and the results were optimized according to multiple quality objectives by the grey system theory. With bending angle, bending radius and hight difference along the axis direction as variables, orthogonal FE analyses were conducted and the minimum and maximum wall thicknes ses of the billets with different sizes were obtained. Taking the minimum and maximum wall thick nesses as two references, the correlation coefficient between the data for reference and those for comparison by the grey system theory reduced multi objectives to a single quality objective, and the average correlation level of every billet facilitated the optimization of size parameters for hydroform ing car beam. The trial production showed that the optimization approach satisfied the need of hy droforming car beams.

Probability estimation based on grey system theory for simulation evaluation

In the evaluation of some simulation systems, only small samples data are gotten due to the limited conditions. In allusion to the evaluation problem of small sample data, an interval estimation approach with the improved grey confidence degree is proposed.On the basis of the definition of grey distance, three kinds of definition of the grey weight for every sample element in grey estimated value are put forward, and then the improved grey confidence degree is designed. In accordance with the new concept, the grey interval estimation for small sample data is deduced. Furthermore,the bootstrap method is applied for more accurate grey confidence interval. Through resampling of the bootstrap, numerous small samples with the corresponding confidence intervals can be obtained. Then the final confidence interval is calculated from the union of these grey confidence intervals. In the end, the simulation system evaluation using the proposed method is conducted. The simulation results show that the reasonable confidence interval is acquired, which demonstrates the feasibility and effectiveness of the proposed method.

Selecting Suitable Heat Source in Refinery for Multi-effect Distillation Based on Grey System Theory

For dealing with high-salinity wastewater in the refinery, the high cost of driving heat source is the disadvantage of multi-effect distillation (MED) so it is of great importance to evaluate the performance of low-temperature heat source for conducting MED and select the optimal temperature for it. Both the MED and the low-temperature heat sources studied in this paper were from a typical refinery located in northwestern China. Besides, a new methodology to evaluate heat sources as the optimal candidate was proposed for MED based on the grey system theory. Five process units, which included 18 fluids of the refinery, were named as the evaluation projects. Three factors, which included safety effects, total costs and characteristics of low-temperature heat sources were determined as the evaluation indexes, the values of which were established through the analyses. The results obtained through the grey correlation analyses have revealed that the grey correlation degrees of these units were 0.661(AVDU), 0.732 (#1 FCCU), 0.618 (#2 FCCU), 0.535 (#1 DCU), and 0.572 (#2 DCU), respectively. Thus, the optimal heat source was provided from #1 FCCU. Through further analyses of the fluids from #1 FCCU, the grey correlation degrees of the fluids were 0.597 (oil and gas at top of tower), 0.714 (recycle oil and gas), and 0.512 (diesel), respectively. Thus, the optimal heat source was the oil and gas recycle stream.

Improve power quality of coal mine power network based on gray system theory

Unified Power Quality Controller（UPQC） was proposed to comprehensively improve power quality of coal mine power network and its basic structure and operation principle was introduced. In order to overcome time lag of Active Power Filter（APF） in compensating harmonic and reactive current, a novel method based on gray system theory was proposed to predict harmonic current and other distortion component. The mathematical model of component to be compensated was constructed by data sequence of distortion component, which could exactly forecast compensation signal of next period. The optimal control strategy was selected according to the principle of output signal approaching component to be compensated as near as possible. Before predicating each time the oldest data was eliminated while the latest data was added to data sequence. Then new predication model was established once again. The results show that the method can always construct mathematical model with variation of system parameters, reflect the latest state of system and not increase calculation quantity. The feasible and effective control strategy can improve power quality of coal mine power network.

Re-examination of the Two-Body Problem Using Our New General System Theory

It is well-known that philosophical conflicts exist among classical mechanics,quantum mechanics and relativistic mechanics.In order to use the framework of general system theory to unify these three mechanics subjects,a new general system theory is developed based on a new ontology of ether and minds as the fundamental existences in the world.The two-body problem is the simplest model in mechanics and in this paper,it is re-examined by using our new general system theory.It is found that the current description of the classical full two-body problem is inappropriate since the observer and the measurement apparatus have not been explicitly considered.After considering these,it is actually a three-body problem while only the special case of the Kepler problem is the two-body problem.By introducing the concepts of psychic force and psychic field,all the possible movement states in the two-body problem can be explained within the framework of classical mechanics.There is no need to change the meanings of many fundamental concepts,such as time,space,matter,mass,and energy as done in quantum mechanics and relativity theory.This points out a new direction for the unification of different theories.

Using Grey System Theory for Earthquake Forecast

By combining conventional grey correlation analysis, grey clustering method and grey forecasting methods with our multi-goal forecast thoughts and the techniques of grey time series processing, we develop six different grey earthquake forecast models in this paper. Using the record of major earthquakes in Japan from 1872 to 1995, we forecast future earthquakes in Japan. We develop an earthquake forecast model. By using the major earthquakes in Japan from 1872 to 1984, we forecast earthquakes from 1985 to 1995 and check the precision of the grey earthquake models. We find that the grey system theory can be applied to earthquake forecast. We introduce the above analysis methods and give a real example to evaluate and forecast. We also further discuss the problems of how to improve the precision of earthquake forecast and how to strengthen the forecast models in future research.

Application of Grey System Theory in Design For Cost (DFC)

Design For Cost (DFC) is a branch of Design For X (DFX). In this paper, wedefined DFC as a design method that analyzed and evaluated the product's life cycle cost (LCC), thenmodified the design to reduce the LCC. Nowadays it is a very difficult thing to obtain LCC data inChina or in developing countries. Statistical methods can not be used because available LCC data arefew. In order to solve this problem, we used grey system theory. Then relations of cost factorswere analyzed in LCC using grey relevant methods, and a GM(1,1) model between design parameters andLCC was established. Using this model, we can estimate and control LCC by changing design parametersat the beginning of the design stage.

Circular Economy Development Mode Based on System Theory

The paper tries to explore circular economy from the viewpoint of the system theory. Circular economy is a kind of complicated economic activity, and it is a wholly new ecotype economy proposed by Western countries after they had summed up many experiences and lessons from traditional economy. It is an entirety and has many layers. It keeps an open and dynamic balance. Because the system theory is the theoretical foundation of circular economy, we should systemically analyze and study circular economy from the macroscopic view, correctly grasp its operational laws, improve its service functions, and realize human beings' sustainable development. The paper introduces the content and general characteristics of the system theory and the idea of circular economy. Then it analyzes circular economy based on the system theory. The paper concludes that the integration of circular economy and the system theory can promote the functions of circular economy.

DISCUSSION ON AVERAGE GENERATION OF TWODIMENSIONAL DATA SEQUENCE IN GREY SYSTEM THEORY

An unequal time interval sequence or a sequence with blanks is usually completed with average generation in grey system theory. This paper discovers that there exists obvious errors when using average generation to generate internal points of non-consecutive neighbours. The average generation and the preference generation of the sequence are discussed, the concave and convex properties show the status of local sequence and propose a new idea for using the status to build up the criteria of choosing generation coefficient. Compared with the general average method of the one-dimensional data sequence, the two-dimensional data sequence is defined and its average generation is discussed, and the coefficient decision method for the preference generation is presented.

Map Building for a Mobile Robot Based on Grey System Theory

In this paper, a new method for mobile robot map building based on grey system theory is presented, by which interpretation and integration of sonar readings can be solved robustly and efficiently. The conception of 'grey number is introduced to model and handle the uncertainty of sonar reading. A new data fusion approach based on grey system theory is proposed to construct environment model. Map building experiments are performed both on a platform of simulation and a real mobile robot. Experimental results show that our method is robust and accurate.