network modeling Articles
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Assessing model efficacy in forecasting EPS of Chinese firms using fundamental accounting variables: a comparative study
In this paper, we compare the forecasting accuracy of two neural network models in forecasting earnings per share of Chinese listed companies based upon fundamental accounting variables. In one neural network model, weights estimated by back propagation were utilised, and in the other model a genetic algorithm was utilised. Based upon a sample of 723 Chinese companies in 22 industries over a ten ...
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Managing and organising collaborative improvement: a system integrator perspective
More than ever, companies are challenged to improve their performance and respond quickly and accurately to changes within the market. Because of external dynamics, competition is moving towards the level of networks of organisations, and thus the individual firm is an inadequate entity for identifying improvements. The concept of continuous improvement must be applied and used in ...
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Business and network models for innovation: strategic logic and the role of network position
Firms increasingly organise their innovation activities in networked environments, including specific models such as supplier-network innovation, coopetition, or open innovation with a large set of stakeholders. These types of business and network models for innovation are often discussed from one of two main approaches – the strategic or the structural. The strategic approach examines the focus ...
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R&D networks: an evaluation framework
R&D networks have been studied and promoted by scholars and policy makers as a way to increase the performance of innovation systems. At the same time, limited attention has been devoted to evaluate their performances. This paper reviews the literature that studied R&D networks from different approaches and suggests a framework to help developing evaluation systems for R&D networks. The ...
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Single hidden layer artificial neural network models versus multiple linear regression model in forecasting the time series of total ozone
Present paper endeavors to develop predictive artificial neural network model for forecasting the mean monthly total ozone concentration over Arosa, Switzerland. Single hidden layer neural network models with variable number of nodes have been developed and their performances have been evaluated using the method of least squares and error estimation. Their performances have been compared with ...
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Requirements for transport network flow models used in reliability analysis
The network reliability of transport systems has been intensively studied in the last two decades. When we discuss network reliability models, the following four categories of topics can be identified: routing and scheduling under uncertain conditions; flow models for degraded and congested networks; evaluation and measurement of reliability; network design and management. Of these, transport ...
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Alternate neural network models in decision making for socio-economic development
Alternate neural network models are used to identify the structure of preferences for development alternatives and their consequences in the cases of Doon Valley and National Capital Region in India in the context of carrying-capacity-based developmental planning. Alternate neural network models are presented as an effective alternative to deal with multi-criteria decision-making situations. The ...
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Pore to continuum upscaling of permeability in heterogeneous porous media using mortars
Pore–scale modelling has become an accepted method for estimating macroscopic properties (such as permeability) that describe flow and transport in porous media. In many cases extracted macroscopic properties compare favourably to experimental measurements. However, computational and imaging restrictions generally limit the network size to the order of 1.0 mm³ and these models often ignore ...
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Determining product differentiation strategies under uncertain environment
Owing to product proliferation and expanding high customer service provision, firms nowadays face severe competitive challenges in globalisation. The revised process or product design often involves delaying products differentiation until later production stages. Form postponement applying fuzzy theory and mathematical programming is implemented to formulate a multi-period, multistage assembly ...
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Fuzzy Logic and Artificial neural network approaches for dissolved oxygen prediction
A study on application of data-driven models namely the rule-based model based on mamdani Fuzzy Logic and Artificial Neural Network model in predicting dissolved oxygen in an effluent-impacted urban river is presented and compared. Combined rule bases were formed from the generated fuzzy rules for input – output mapping. Predictability of both the models was good with better performance for ...
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Neural network model for identification of societal preference of environmental issues
A new method for identification of preferences of environmental issues using the societal approach is suggested. The preferences assigned by different economic groups to 11 environmental issues are obtained through analysis of linguistically stated relative rankings using fuzzy partial ordering method. The system identification technique based on neural networks is used to identify a logical ...
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Anglian Ely - Adaptive Networks with Dynamic Topology Case Study
Anglian Water (AW) were keen to understand and validate the network model and dynamic network behaviour of two adjacent DMA’s. This included simulating the installation and operation of a dynamic boundary valve. In order to implement and maintain the operation of the adjacent DMAs with dynamic topology, a sufficiently accurate hydraulic network model was required to calculate and evaluate ...
By Inflowmatix
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Exploring the applicability of electronic markets to port governance
The paper explores the rationale of embracing e-Governance models as a mean to improve port policy and decision making towards enhanced port performance and competitiveness. The paper establishes both the significance and the applicability of advanced port e-Governance models, based on e-markets typologies. The devised theoretical framework suggests that within the evolving variation of port ...
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Internationalisation of the small and medium family firm in Japan
In recent years, small family businesses in Japan are under enormous pressure to expand outside of home country due to various reasons. The purpose of this paper is to look for the appropriate internationalisation path for small and medium family firms in Japan as well as other strategic internationalisation factors and determinants. The study, qualitative research was conducted using case study ...
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A hybrid adaptive time-delay neural network model for multi-step-ahead prediction of sunspot activity
The availability of accurate empirical models for multi-step-ahead (MS) prediction is desirable in many areas. Some ANN technologies, such as multiple-neural network, time-delay neural network (TDNN), and adaptive time-delay neural network (ATNN), have proven successful in addressing various complicated problems. The purpose of this study was to investigate the applicability of neural network MS ...
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Enhancing accuracy of autoregressive time series forecasting with input selection and wavelet transformation
Autoregressive time series forecasting is common in different areas within water resources, which include hydrology, ecology, and the environment. Simple forecasting models such as linear regression have the advantage of fast runtime, which is attractive for real-time forecasting. However, their forecasting performance might not be acceptable when a non-linear relationship exists between ...
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Clusters of supernova stars in knowledge-based spaces: value creation through cooperation
The process of value creation out of the acquisition, transfer and exploitation of scientific knowledge has become a major challenge for developed economies. Knowledge institutions like universities and R&D centres are important actors in this context. This paper offers a novel contribution to the assessment of the regional-economic importance of local and regional knowledge centres in the ...
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A hybrid model coupled with singular spectrum analysis for daily rainfall prediction
A hybrid model integrating artificial neural networks and support vector regression was developed for daily rainfall prediction. In the modeling process, singular spectrum analysis was first adopted to decompose the raw rainfall data. Fuzzy C-means clustering was then used to split the training set into three crisp subsets which may be associated with low-, medium- and high-intensity rainfall. ...
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An intelligent neural network model for evaluating performance of immobilized cell biofilter treating hydrogen sulphide vapors
Biofiltration has shown to be a promising technique for handling malodours arising from process industries. The present investigation pertains to the removal of hydrogen sulphide in a lab scale biofilter packed with biomedia, encapsulated by sodium alginate and poly vinyl alcohol. The experimental data obtained under both steady state and shock loaded conditions were modelled using the basic ...
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Local vs. external training of neuro-fuzzy and neural networks models for estimating reference evapotranspiration assessed through
k -fold testingThe improvement of methods for estimating reference evapotranspiration (ET0) requiring few climatic inputs is crucial, due to the partial or total lack of climatic inputs in many situations. The current paper compares the effect of local and external training procedures in neuro-fuzzy and neural network models for estimating ET0 relying on two input combinations considering k-fold testing. ...
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