Quantitative System Models Research Articles

Design of Quantitative Trading System Based on Data Mining Method under Software and High-Performance Computing

The size of funds managed by all hedge funds in the world has exceeded 2.7 trillion US dollars. The funds of various funds and asset management products managed by quantitative investment account for about 30% of the total global trading volume, and in various large stock exchanges around the world, various quantitative investment methods contribute nearly 50% volume of transactions. The construction of a quantitative trading strategy requires first statistical analysis of the information in the securities and futures market and then backtesting the quantitative model with historical data. In view of the practical application of quantitative trading, this study designs a quantitative trading system based on the data mining method. The main development tool used is the numerical computing software MATLAB, and four cores are designed: quantitative stock selection, strategy backtesting, time-series analysis, and portfolio management. The system supports modules for simple trading decisions. It abandons the traditional method of predicting the absolute value of the future price of stock index futures and adopts a new method of predicting the future price trend of stock index futures. This method avoids the huge impact of the accuracy of the absolute value of the prediction on the final investment in the traditional method and also reduces the high dependence of investors on the accuracy of the absolute value. This study also introduces the support-vector machine algorithm in data mining and the quantitative trading system model in data mining. The accuracy of investment transactions in the experiment is also simulated by using the support-vector machine.

Quantitative Research on the Form of Traditional Villages Based on the Space Gene—A Case Study of Shibadong Village in Western Hunan, China

Traditional villages are the place where national culture is nurtured and inherited. Due to the acceleration of urbanization, the protective exploitation of traditional villages is an urgency in many regions of the world. Under the perspective of the “Space Gene”, we define the connotation of the traditional village space gene, which refers not only to a space combination model, but also the basic inheritance unit of the sustainable development of traditional villages. We further propose the Quantitative Inheritance System Model of Traditional Village Space Genes, which reveals the logic behind the formation of traditional village material forms and builds a quantitative index system for traditional village forms. We take Shibadong Village as an example to prove the model. The results demonstrate that although the four camps in Shibadong Village belong to the same ethnic group and the same village, there are still apparent differences in morphological features. Through the model, we can turn from the “built form” research from the perspective of material space to the “deep structure” research behind it, which can provide scientific guidance for the planning and designs of traditional villages to inherit the history and culture and to protect the diversity of world culture.

Actors, decision-making, and institutions in quantitative system modelling

Increasing realism in quantitative system modelling with respect to the representation of actors, decision-making, and institutions is critical to better understand the transition towards a low-carbon sustainable society. Yet, studies using quantitative system models, which have become a key analytical tool to support sustainability and decarbonization policies, focus on outcomes, therefore overlooking the dynamics of the drivers of change. We explore opportunities that arise from a deeper engagement of quantitative systems modelling with social science. We argue that several opportunities for enriching the realism in model-based scenario analysis can arise through model refinements oriented towards a more detailed approach in terms of actor heterogeneity, as well as through integration across different analytical and disciplinary approaches. Several opportunities that do not require major changes in model structure are ready to be seized. Promising ones include combining different types of models and enriching model-based scenarios with evidence from applied economics and transition studies.

Energy for Adaptation: Connecting the Paris Agreement with the Sustainable Development Goals

Increased effort to cope with the rapidly emerging impacts of climate change is urgently needed. Whether adaptation bears the risk of inducing a negative feedback loop through its energy requirements has not been investigated. Here we examine the Nationally Determined Contributions submitted by world governments under the Paris Agreement with the aim of identifying the adaptation options associated with energy use and of defining energy use for adaptation. By linking the resulting options to the United Nations' Sustainable Development Goals, through the related targets and indicators, we evaluate the extent to which energy use for adaptation facilitate progress towards sustainability. Drawing from the relevant literature on vulnerability and energy, we provide new evidence on the role that energy plays in the context of adaptation, proposing a framework that connects adaptation, mitigation, and sustainable development through the lens of the energy requirements of adaptation strategies. Results highlight priority policy actions to promote climate-development synergies and indicate where quantitative system models could focus in order to integrate adaptation energy needs in future energy scenarios.

Evaluating sustainability transitions pathways: Bridging analytical approaches to address governance challenges

The paper sets out a proposal for bridging and linking three approaches to the analysis of transitions to sustainable and low-carbon societies: quantitative systems modelling; socio-technical transition analysis; and initiative-based learning. We argue that each of these approaches presents a partial and incomplete picture, which has implications for the quality and usefulness of the insights they can deliver for policy and practice. A framework for bridging these different approaches promises to enrich each of the approaches, while providing the basis for a more robust and complete analysis of sustainable transitions pathways that serves better to address questions and dilemmas faced by decision-makers and practitioners. We elaborate five key challenges for the analysis and governance of transitions pathways, and compare the three approaches in relation to each of these. We suggest an integration strategy based on alignment, bridging, and iteration, arguing that a structured dialogue between practitioners of different approaches is needed. In practical terms, such a dialogue would be organised around three areas of joint knowledge production: defining common analytical or governance problems to be tackled through integration; establishing shared concepts (boundary objects); and establishing operational bridging devices (data and metrics, pathways evaluation and their delivery). Such processes could include experts and societal partners. We draw conclusions about future research perspectives and the role of analysis in transitions governance.

Quantitative proteomics and network analysis of SSA1 and SSB1 deletion mutants reveals robustness of chaperone HSP70 network in Saccharomyces cerevisiae.

Molecular chaperones play an important role in protein homeostasis and the cellular response to stress. In particular, the HSP70 chaperones in yeast mediate a large volume of protein folding through transient associations with their substrates. This chaperone interaction network can be disturbed by various perturbations, such as environmental stress or a gene deletion. Here, we consider deletions of two major chaperone proteins, SSA1 and SSB1, from the chaperone network in Sacchromyces cerevisiae. We employ a SILAC‐based approach to examine changes in global and local protein abundance and rationalise our results via network analysis and graph theoretical approaches. Although the deletions result in an overall increase in intracellular protein content, correlated with an increase in cell size, this is not matched by substantial changes in individual protein concentrations. Despite the phenotypic robustness to deletion of these major hub proteins, it cannot be simply explained by the presence of paralogues. Instead, network analysis and a theoretical consideration of folding workload suggest that the robustness to perturbation is a product of the overall network structure. This highlights how quantitative proteomics and systems modelling can be used to rationalise emergent network properties, and how the HSP70 system can accommodate the loss of major hubs.

Exploring possible transition pathways for hydrogen energy: A hybrid approach using socio-technical scenarios and energy system modelling

Hydrogen remains an important option for long-term decarbonisation of energy and transport systems. However, studying the possible transition paths and development prospects for a hydrogen energy system is challenging. The long-term nature of technological transitions inevitably means profound uncertainties, diverging perspectives and contested priorities. Both modelling approaches and narrative storyline scenarios are widely used to explore the possible future of hydrogen energy, but each approach has shortcomings.This paper presents a hybrid approach to assessing hydrogen transitions in the UK, by confronting qualitative socio-technical scenarios with quantitative energy systems modelling, through a process of ‘dialogue’ between scenario and model. Three possible transition pathways are explored, each exploring different uncertainties and possible decision points. Conclusions are drawn for both the future of hydrogen, and on the value of an approach that brings quantitative formal models and narrative scenario techniques into dialogue.

Supply Quantitative Model à la Leontief

This paper focuses on the supply quantitative model system of input–output, which is equivalent to the demand quantitative model system of Leontief. This model allows us to define the total supplied quantities of commodities for any given supplied quantity of primary factors, and consequently enables us to define the final uses of commodities. The supply quantitative model is based on the direct output coefficients of primary factors. The Hadamard Product is also used. The quantitative supply system models might be useful tools in planning the economics of countries that have higher unemployment of primary factors, especially labour.

Interaction analysis for MIMO nonlinear systems based on a fuzzy basis function network model

This paper describes an interaction analysis method for a general multi-input multi-output (MIMO) nonlinear system based on its fuzzy rule-based model. Most real-world multivariable systems are nonlinear, complex and time varying. The multiple system input–output variables interact and sometime even fight against each other, causing significant challenges for system control and optimization. Especially in many practical applications, the accurate quantitative system model is not available or difficult to obtain, which subsequently makes it impossible to analyze the system multivariable interaction characteristics. In this paper, the nonlinear MIMO system is first modeled by fuzzy basis function networks (FBFN) based on a set of linguistic IF–THEN rules or data. The multivariable interaction property is analyzed locally around the operating point based on the relative gain Array (RGA), which is systematically formulated using the system steady-state gain values. Two simulation examples of chemical distillation columns illustrate the system interaction degree obtained by the proposed method is in a sufficient accuracy compared with the result calculated from the system explicit mathematical model, which indicates the applicability of the proposed method as an alternative way to derive the system multivariable interaction when the system mathematical model is not available.

Integrative modelling approaches for analysis of impact of multifunctional agriculture: A review for France, Germany and The Netherlands

This paper reviews integrative modelling approaches which were developed to analyze the impact of multifunctional agriculture, or which may be used as such. The approaches are integrative in combining multiple goals of agriculture, and confronting these with current or potential performance of agricultural land-use systems at different spatial scales. The paper focuses on France, Germany and The Netherlands, countries with a track record in quantitative systems modelling, to identify convergence of concepts and technologies applicable to assessment of multifunctional agriculture and to establish shortcomings through analysis and comparison of 15 integrative modelling cases. An analytical framework for comparison is applied, based on a conceptual model of goal-oriented evaluation of agriculture. Results demonstrate unexpectedly large differences between countries in the number of integrative models; the nature of agro-ecological or bio-economic relations used, and target audience. Common elements were a focus on methodology development rather than answering questions of specific clients, limited attention for model evaluation and impact analysis, and an imbalanced attention for economic and abiotic environmental indicators at the expense of biotic, landscape and social indicators. None of the approaches specifically addressed multifunctionality of agriculture. In the discussion we argue that to be relevant research efforts aimed at supporting policy development for multifunctional agriculture cannot concentrate on filling gaps in knowledge and technology alone, but need to concern the process of utilization of knowledge as well.

Control of chaos in excitable physiological systems: A geometric analysis.

Model-independent chaos control techniques are inherently well-suited for the control of physiological systems for which quantitative system models are unavailable. The proportional perturbation feedback (PPF) control paradigm, which uses electrical stimulation to perturb directly the controlled system variable (e.g., the interbeat or interspike interval), was developed for excitable physiological systems that do not have an easily accessible system parameter. We develop the stable manifold placement (SMP) technique, a PPF-type technique which is simpler and more robust than the original PPF control algorithm. We use the SMP technique to control a simple geometric model of a chaotic system in the neighborhood of an unstable periodic orbit (UPO). We show that while the SMP technique can control a chaotic system that has UPO dynamics which are characterized by one stable manifold and one unstable manifold, the success of the SMP technique is sensitive to UPO parameter estimation errors. (c) 1997 American Institute of Physics.

A Comparison of Respirator Fit Factors Determined by Portable Condensation Nuclei Counting and Forward Light-Scattering Photometric Methods

Abstract The purpose of this study was to compare fit factors determined by a recognized photometer quantitative fit test system (Model 264, Dynatech-Frontier Corp.) and a portable condensation nuclei counter respirator fit test instrument (Portacount, TSI, Inc.). The study was performed by conducting sequential fit tests with the two methods on human subjects wearing the same respirator at the same fitting. The fit factors obtained by the two methods were compared by several statistical tests. The results of these analyses indicated that there was good agreement in determining pass/fail at a critical fit factor. It was further concluded that fit factors for groups of wearers measured by the condensation nuclei counter instrument are comparable to those obtained by the photometer method.