Hierarchical Systems Theory Research Articles

Adaptations in a hierarchical food web of southeastern Lake Michigan

Two issues in ecological network theory are: (1) how to construct an ecological network model and (2) how do entire networks (as opposed to individual species) adapt to changing conditions? We present a novel method for constructing an ecological network model for the food web of southeastern Lake Michigan (USA) and we identify changes in key system properties that are large relative to their uncertainty as this ecological network adapts from one time point to a second time point in response to multiple perturbations. To construct our food web for southeastern Lake Michigan, we followed the list of seven recommendations outlined in Cohen et al. [Cohen, J.E., et al., 1993. Improving food webs. Ecology 74, 252–258] for improving food webs. We explored two inter-related extensions of hierarchical system theory with our food web; the first one was that subsystems react to perturbations independently in the short-term and the second one was that a system's properties change at a slower rate than its subsystems’ properties. We used Shannon's equations to provide quantitative versions of the basic food web properties: number of prey, number of predators, number of feeding links, and connectance (or density). We then compared these properties between the two time-periods by developing distributions of each property for each time period that took uncertainty about the property into account. We compared these distributions, and concluded that non-overlapping distributions indicated changes in these properties that were large relative to their uncertainty. Two subsystems were identified within our food web system structure ( p < 0.001). One subsystem had more non-overlapping distributions in food web properties between Time 1 and Time 2 than the other subsystem. The overall system had all overlapping distributions in food web properties between Time 1 and Time 2. These results supported both extensions of hierarchical systems theory. Interestingly, the subsystem with more non-overlapping distributions in food web properties was the subsystem that contained primarily benthic taxa, contrary to expectations that the identified major perturbations (lower phosphorous inputs and invasive species) would more greatly affect the subsystem containing primarily pelagic taxa. Future food-web research should employ rigorous statistical analysis and incorporate uncertainty in food web properties for a better understanding of how ecological networks adapt.

A strategic planning methodology

The aim of this paper is to develop a method for strategic transport planning, which can be applied from the local up to the international level. A newly developed strategic transport plan is verified in comparison to four strategic transport plans, i.e. on the national level: Austria's Generalverkehrsplan-Österreich 2002, the German Bundesverkehrswegeplan 2003, and from Switzerland the Sachplan Schiene/öV [BAV, 2002. Sachplan Schiene/öV—Konzeptteil (Teile I bis IV and Anhänge)—Vernehmlassungsentwurf, September 2002, Bern, Schweiz, Bundesamt für Verkehr] and the Sachplan Strasse [Astra, 2002. Der Sachplan Strasse, September 2002, Bern, Bundesamt für Strassen, Bundesamt für Raumentwicklung]; on the international level, the EU White paper on transport policy [European Commission, 2001. White paper—European transport policy for 2010: time to decide. Technical Report, EU]. The methodology is based on a combination of control theory and hierarchical systems theory, which the former provides a stringent-ordered structure of the complexity between objectives, measures and indicators and the latter a consistent hierarchy for the involved topics and issues. The method allows an assessment and comparison with the above mentioned plans, which is required if a consistent transport strategy should be achieved between these levels.

The Dialectic of Bottom-up and Top-down Emergence in Social Systems

In this paper we will present a theoretical explanation of the relationship between so-called individual emergence and the emergence of social systems. We want to take as our point of departure the assumption that from the perspective of hierarchical systems theory self-organization on the level of social systems includes a bottom-up process as well as a top-down process. The bottom-up process refers to what in sociology is called agency, the top-down process refers to what is called structure. We will show that it is convenient to suggest that these processes be linked in a dialectical manner. In this respect we will discuss problems of determinism and indeterminism. This is the background against which we will try to clarify the notion of individual emergence. Our rather general considerations will be illustrated by how ideology, that is consciousness in a collective as well as an individual sense, is conceived of by a number of theories and how it should be conceived of when aspects of self-organization are included. We will conclude with a statement that makes clear why consciousness is a property of individuals that emerges only when individuals participate in society and why society emerges only when individuals are endowed with consciousness.

BIOCOMPLEXITY AND GLOBAL GEOGRAPHIC INFORMATION MONITORING

The biocomplexity problem in the global “environment-society” system is examined from the point of view of the theory of complex hierarchical systems. The hierarchy of space and time scales is simulated in the terms of the quantity of information, diversity of elements, dynamic stability of biogeochemical cycles, and relations between sets of elements. A simulative-methodological model of biocomplexity dynamics based on the correlations between basic elements of the global “environment-society” system is constructed. The interrelationship among biocomplexity, stability, and viability criteria is analyzed. The possibility of computing a biocomplexity index via satellite monitoring is assessed.

Practical Instance of State Design in Reconstructing Region

The paper describes the applying of theory of hierarchical multilevel systems (aed theory, hierarchical mathematics) to the process of State design in reconstructing regions. Aed theory allows to construct the key statute of States and States unions which connects the descriptions of State internal construction (defined in space of natural, demographical, engineering and knowledge levels), State power institutes, and State external activity. The using of the key statute gives a chance to elaborate the program of State reconstructing of concrete country (Belarus) in line with the requirements of State design process. This method of State design can help to avoid in the reconstructing of single State the hard errors, which can turn this State into the source of world instability. The program is cohered with the strategies of existent institutions in world and regional scales (the United Nations, European Union and other).

Optimal Control of High Pressure Gas Networks by Two Different Methods

The aim of the paper in to present two different methods implemented for optimal control of high pressure gas networks. The problem is large scale and highly non-linear in both objective function and constraints. First method is based on the Lagrangian dual problem. Second method uses hierarchical systems theory. Discrete state equation for the case in which output pressure are treated as elements of the control vector has been fonnulated. Elements of the state vector are non - outlet node pressures and flows through units. In both cases algorithms for optimal control over periods up to a day have been developed. Results are included for some realistic problems.

Stimulation and decision-making in the active system theory: Review of problems and new results

The recent two decades witnessed intensive research in the area of organizational (socio-economic) mechanisms. Foreign researchers concentrated mostly on collective decision-making and contract theories. In the former USSR these problems were considered within the informational theory of hierarchical systems and the theory of active systems that are, basically, a unique area studying active human behavior in organizational systems. By activity we mean the human ability of choosing purposefully actions (states), manipulating data (conscientious representation of doubtful information for making preferential decisions) and, finally, foresight in decision-making.

A diagnostic expert system prototype for CIM

This paper describes the Diagnostic System Prototype (DSP), consisting of a deep knowledge base and several shallow knowledge bases, and shows how it works. Based on the theory of hierarchical systems and hybrid diagnostic reasoning, the DSP tries to find a cause(s) for an observed symptom in CIM (Computer-Integrated Manufacturing), using the concept of entropy. The entropy is calculated using test costs and degrees of belief for each rule in the shallow knowledge bases. The DSP is expected to be applicable to different domains other than just the manufacturing environment.

Hierarchical multiobjective analysis for large-scale systems: Review and current status

Large-scale systems are often characterized by hierarchical structure, and they usually have multiple objectives that are noncommensurable. Two well-known approaches to the analysis of systems—hierarchical system theory and multiobjective optimization—have been developed to deal with these two aspects of large-scale systems. The past decade has seen an increasing concern with the integration of these two approaches into a unified framework for large-scale systems, leading to the emergence of a new field known as hierarchical multiobjective analysis. This paper provides a systematic review of the literature associated with the modeling and optimization of large-scale systems, focusing on research based on the hierarchical multiobjective approach, the overlapping decomposition approach, and the multimodel approach. A large number of recently published papers that fall within these areas are reviewed.

Hierarchical Multiobjective Analysis for Large-Scale Systems: Current Status

Large-scale systems are often characterized by hierarchical structure, and they usually have multiple objectives that are noncommensurable. Two well-known approaches to the analysis of systems--hierarchical system theory and multiobjective optimization--have been developed to deal with these two aspects of large-scale systems. The past decade has seen an increasing concern with the integration of these two approaches into a unified framework for large scale systems, leading to the emergence of a new field known as hierarchical multiobjective analysis. This paper provides a systematic survey of the literature associated with the modeling and optimization of large scale systems, focusing on research based on the hierarchical multiobjective approach, the overlapping decomposition approach, and the multimodel approach. A large number of recently published papers that fall within these areas are reviewed.

A Multiobjective Optimization Approach to a Design Problem of Heat Insulation for Thermal Distribution Piping Network Systems

A multiobjective optimization method is applied to a design problem of heat insulation for thermal distribution piping network systems. As the system’s multiple design objectives, the following two mutually conflicting and noncommensurable objective functions are considered simultaneously: (a) minimization of the total amount of heat loss from the whole system, and (b) minimization of the total volume of heat insulating material installed into the whole system. First, for a piping system of fundamental network structure, the set of Pareto optimal solutions is derived for the optimal design problem mentioned above by adopting the weighting method and the generalized reduced gradient algorithm. Second, for the purpose of investigating the same problem for piping systems of more complex network structure, a computer-aided interactive planning system is developed based on decomposition and coordination principles in the theory of hierarchical multilevel systems. Lastly, the validity and the effectiveness of the optimal design method proposed here are ascertained through numerical studies for some typical piping network systems.

Axiomatic theory of hierarchical systems

An axiomatic theory of hierarchical systems is presented. This theory is intended to apply to general multilevel systems and to provide a framework for mathematical modeling of such systems. As an example, several possible implications for Miller's (1978) living systems theory are mentioned. The mathematical development of the general theory is continued by imposing a restriction of vertical linearity. Several theorems relating to issues of control are proved for vertically linear systems. A theorem showing the feasibility of environmental interaction via cyclic time-lagged correlations between system variables is proved.

Decomposition and Aggregation in Hierarchical Systems

One problem facing hierarchical system theory is that the allowed exact decompositions may result in problems which are too complex to be feasibly implemented. The approach of this paper is to allow aggregations of the exact decomposition. The questions of convergence of the simplified iteration and the nearness of the resulting solution to the true solution are addressed.

A Hierarchical Strategy for Traffic Control in Urban Networks

The paper presents an application of hierarchical multi level system theory in network traffic control problem solving. Street network is represented by a directed graph. Nodes represent signalized intersections, and arcs represent street sections between adjacent signal ized intersections. Traffic process is described by delay-difference-of-offset functions. Loop constraints on offsets are incorporated in the model. The problem is to minimize loses (delay) in the network. Two-level hierarchical system structure is used in solving the problem. For subproblems coordination interaction balance principle is applied. It is shown that tasks performed by first and second level subsystems are quite simple, and suitable for real time control.

Parallel Processing Concepts for Distributed Computer Control Systems

It is proposed to utilize the spare processing power embedded in a real-time computer control network for the computation of a common distributed task in a co-ordinated manner. The algorithm of Hierarchical System Theory is used as a medium to explore the principles involved in time-sharing this distributed background job with the computation of the real-time control algorithm. An interconnection structure is put forward to satisfy the resulting data-processing requirements.

THE LAW OF REQUISITE HIERARCHY

A cybernetic theory of hierarchical social systems is given, starting from an extension of Ashby's general theory of regulation and control to amplifying regulation. Regulation and control in human society are then discussed and the conditions for the existence of social classes and social hierarchy examined.

Hierarchical control of power distribution systems

The concepts of hierarchical system theory, in conjunction with power system engineering, have been applied to enable the real-time control of a large-scale power distribution system.1 The control objective of the distribution system consists of security (equipments protection) and operation (continuity of service) requirements to be satisfied within the feasible control boundaries for all substations composing the distribution system. The overall control strategy for each substation is decomposed into independent control functions which are ordered (ranked) to meet a hierarchy of control requirements specified by the system's physical operation. This approach was adopted not only to simplify the real-time control problem solution, but also was necessitated by the requirement that a partial feasible solution be provided which meets higher priority objectives when a total feasible solution does not exist. This paper describes, in the hierarchical framework, the physical process, the network decomposition and modeling, the control decomposition and criteria, and the control procedure along with numerical results.

Error performances of the multilevel world integrated model (WIM) as applied to Nigeria

From the Table 2 results, our conclusion is that the level of error propagation tends to be much smaller in the model whose technique is based on the multilevel hierarchical systems theory than in the one that adopts the naive Forecast for Year n Equals Statistics for Year n-1 Approach (but for one case where the latter resulted in a smaller error) or the technique of parameter estimations based on econometric theory.

Analysis of complex systems

It is argued that a complex system of the kind arising in industry is intrinsically structured: that is to say it may be regarded as an interconnected assembly of subsystems. By exploiting this structure it is possible to decompose the problem of controlling a complex system into a series of interlinked subproblems of manageable size. Each subproblem can be solved largely independently of the others, with the interconnections between the subproblems being accounted for by some kind of coordination procedure. Such an approach to complex systems analysis leads naturally to a study of decentralized and hierarchical control methods and as there is no doubt that industrial management has a hierarchical structure it is important to assess the usefulness of the techniques of hierarchical systems theory in the management of complex industrial systems. In cases where the overall management problem can be posed as a linear or non-linear programming problem there is a good body of theory to support the decentralized approach and the basic concepts of this theory are illustrated in this paper by consideration of decentralized optimization of an interconnected production system. It is shown that effective optimal coordination of such a system is difficult to achieve if the subsystems are nonlinear but that satisfactory coordination procedures may be devised if proper account is taken of the slackness which usually exists in the interconnections between real systems. The need to assess the usefulness of these ideas in a real industrial environment is stressed.

Hierarchical modelling of acclimatory processes

The term acclimation has been used with several connotations in the field of acclimatory physiology. An attempt has been made, in this paper, to define precisely the term “acclimation” for effective modelling of acclimatory processes. Acclimation is defined with respect to a specific variable, as cumulative experience gained by the organism when subjected to a step change in the environment. Experimental observations on a large number of variables in animals exposed to sustained stress, show that after initial deviation from the basal value (defined as “growth”), the variables tend to return to basal levels (defined as “decay”). This forms the basis for modelling biological responses in terms of their growth and decay. Hierarchical systems theory as presented by Mesarovic, Macko & Takahara (1970) facilitates modelling of complex and partially characterized systems. This theory, in conjunction with “growth-decay” analysis of biological variables, is used to model temperature regulating system in animals exposed to cold. This approach appears to be applicable at all levels of biological organization. Regulation of hormonal activity which forms a part of the temperature regulating system, and the relationship of the latter with the “energy” system of the animal of which it forms a part, are also effectively modelled by this approach. It is believed that this systematic approach would eliminate much of the current circular thinking in the area of acclimatory physiology.