Understanding innovation diffusion and adoption strategies in megaproject networks through a fuzzy system dynamic model

Innovation and knowledge diffusion in megaprojects is one of the most complicated issues in project management.Compared with conventional projects,megaprojects typically entail large-scale investments,long construction periods,and conflicting stakeholder interests,which result in a distinctive pattern of innovation diffusion.However,traditional investigation of innovation diffusion relies on subjective feedback from experts and frequently neglects inter-organizational knowledge creation,which frequently emerges in megaprojects.Therefore,this study adopted project network theory and modeled innovation diffusion in megaprojects as intra-and interorganizational learning processes.In addition,system dynamics and flizzy systems were combined to interpret experts9 subject options as quantitative coefficients of the project network model.This integrated model will assist in developing an insightful understanding of the mechanisms of innovation diffusion in megaprojects.Three typical network structures,namely,a traditional megaproject procurement organization(TMO),the environ megaproject organization(EMO),and an integrated megaproject organization(IMO),were examined under six management scenarios to verify the proposed analytic paradigm.Assessment of project network productivity suggested that the projectivity of the TMO was insensitive to technical and administrative innovations,the EMO could achieve substantial improvement from technical innovations,and the 1MO trended incompatibly with administrative innovations.Thus,industry practitioners and project managers can design and reform agile project coordination by using the proposed quantitative model to encourage innovation adoption and reduce productivity loss at the start of newly established collaborations.

Modeling and Analysis of Mechanization Projects of Wheat Production by GERT Networks

In crop production systems,all operations such as seed bed preparation,etc.,must be accomplished on time,if yield reduction and low quality product are to be avoided.Therefore all operations in mechanized cropping projects require precise scheduling,planning and management.The basic approach in all scheduling techniques is to form a network of activities and events relationships that graphically portrays the sequential relations between the tasks in a project.Such a network would as a powerful tool available a farm manager to plan,schedule,monitor and control a project.Since GERT（Graphical Evaluation and Review Technique） networks have most of advantages associated with networks and available system analyst in exact evaluation of certain types of networks,in this research it was used and mechanized wheat production system was simulated,modeled and analyzed.Critical activities,events and path were determined.Results showed that the network model was able to answer any statistic questions concerning with the project.Network models,particularly GERT networks are increasingly powerful tool for modeling,scheduling,planning,controlling,and analyzing of agricultural mechanization projects.

Projective synchronization of a complex network with different fractional order chaos nodes

Based on the stability theory of the linear fractional order system, projective synchronization of a complex network is studied in the paper, and the coupling functions of the connected nodes are identified. With this method, the projective synchronization of the network with different fractional order chaos nodes can be achieved, besides, the number of the nodes does not affect the stability of the whole network. In the numerical simulations, the chaotic fractional order Lu system, Liu system and Coullet system are chosen as examples to show the effectiveness of the scheme.

Generalized projective synchronization of two coupled complex networks of different sizes

We investigate a new generalized projective synchronization between two complex dynamical networks of different sizes. To the best of our knowledge, most of the current studies on projective synchronization have dealt with coupled networks of the same size. By generalized projective synchronization, we mean that the states of the nodes in each network can realize complete synchronization, and the states of a pair of nodes from both networks can achieve projective synchronization. Using the stability theory of the dynamical system, several sufficient conditions for guaranteeing the existence of the generalized projective synchronization under feedback control and adaptive control are obtained. As an example, we use Chua’s circuits to demonstrate the effectiveness of our proposed approach.

Adaptive function projective synchronization of uncertain complex dynamical networks with disturbance

We investigate the problem of function projective synchronization （FPS） in drive–response dynamical networks with non-identical nodes. An adaptive controller is proposed for the FPS of complex dynamical networks with uncertain parameters and disturbance. Not only are the unknown parameters of the networks estimated by the adaptive laws obtained from the Lyapunov stability theory and Taylor expansions, but the unknown bounded disturbances are also simultaneously conquered by the proposed control. Finally, a numerical simulation is provided to illustrate the feasibility and effectiveness of the obtained result.

A NEW APPROACH FOR UNSUPERVISED RESTORING IMAGES BASED ON WAVELET-DOMAIN PROJECTION PURSUIT LEARNING NETWORK

The Wavelet-Domain Projection Pursuit Learning Network (WDPPLN) is proposedfor restoring degraded image. The new network combines the advantages of both projectionpursuit and wavelet shrinkage. Restoring image is very difficult when little is known about apriori knowledge for multisource degraded factors. WDPPLN successfully resolves this problemby separately processing wavelet coefficients and scale coefficients. Parameters in WDPPLN,which are used to simulate degraded factors, are estimated via WDPPLN training, using scalecoefficients. Also, WDPPLN uses soft-threshold of wavelet shrinkage technique to suppress noisein three high frequency subbands. The new method is compared with the traditional methodsand the Projection Pursuit Learning Network (PPLN) method. Experimental results demonstratethat it is an effective method for unsupervised restoring degraded image.

INTRODUCTION OF YES NETWORK PROJECT:A LEGACY OF IYPE TRIENNIUM

YES congress 2009 aims to involve future decision makers and scientists in order to create long-term actions toward sustainability and restoration of earth systems,and to build long-term bridges between the scientific community and future decision makers.

ZTE Selected by BelTelecom for GPON National Broadband Network Project

ZTE Corporation announced on May 30, 2011 that it had won BelTelecom＇s national broadband network project in Belarus.

Adaptive generalized matrix projective lag synchronization between two different complex networks with non-identical nodes and different dimensions

The adaptive generalized matrix projective lag synchronization between two different complex networks with non-identical nodes and different dimensions is investigated in this paper. Based on Lyapunov stability theory and Barbalat＇s lemma, generalized matrix projective lag synchronization criteria are derived by using the adaptive control method. Furthermore, each network can be undirected or directed, connected or disconnected, and nodes in either network may have identical or different dynamics. The proposed strategy is applicable to almost all kinds of complex networks. In addition, numerical simulation results are presented to illustrate the effectiveness of this method, showing that the synchronization speed is sensitively influenced by the adaptive law strength, the network size, and the network topological structure.

Generalized projective synchronization of fractional-order complex networks with nonidentical nodes

This paper investigates the synchronization problem of fractional-order complex networks with nonidentical nodes. The generalized projective synchronization criterion of fractional-order complex networks with order 0 〈 q 〈 1 is obtained based on the stability theory of the fractional-order system. The control method which combines active control with pinning control is then suggested to obtain the controllers. Furthermore, the adaptive strategy is applied to tune the control gains and coupling strength. Corresponding numerical simulations are performed to verify and illustrate the theoretical results.

"3Ns" Shelterbelt Network Project

In China’s three northern regions of the Northwest, North and Northeast (3Ns), there are 1.33 million sq km of desert and sand land, forming a 5,000-km-long wind-sand belt. In 1978, the Chinese government decided to build the "3Ns" shelterbelt network. The project covers 13 provinces, autonomous regions and cities including Xinjiang, Qinghai, Gansu, Ningxia, Shaanxi, Inner Mongolia, Shanxi, Hebei, Beijing, Tianjin, Liaoning, Jilin and Heilongjiang, eovering an area of 4.06 million sq km, 42％ of the country’s total land. It plans to complete the project in 73 years, in three phases: the first phase

Joint optimization scheduling for water conservancy projects incomplex river networks

In this study, we simulated water flow in a water conservancy project consisting of various hydraulic structures, such as sluices, pumping stations, hydropower stations, ship locks, and culverts, and developed a multi-period and multi-variable joint optimization scheduling model for flood control, drainage, and irrigation. In this model, the number of sluice holes, pump units, and hydropower station units to be opened were used as decision variables, and different optimization objectives and constraints were considered. This model was solved with improved genetic algorithms and verified using the Huaian Water Conservancy Project as an example. The results show that the use of the joint optimization scheduling led to a 10% increase in the power generation capacity and a 15% reduction in the total energy consumption. The change in the water level was reduced by 0.25 m upstream of the Yundong Sluice, and by 50% downstream of pumping stations No. 1, No. 2, and No. 4. It is clear that the joint optimization scheduling proposed in this study can effectively improve power generation capacity of the project, minimize operating costs and energy consumption, and enable more stable operation of various hydraulic structures. The results may provide references for the management of water conservancy projects in complex river networks.

Modified Function Projective Synchronization of Complex Networks with Multiple Proportional Delays

This paper deals with the modified function projective synchronization problem for general complex networks with multiple proportional delays. With the existence of multiple proportional delays, an effective hybrid feedback control is designed to attain modified function projective synchronization of networks. Numerical example is provided to show the effectiveness of our result.

A uniform framework of projection and community detection for one-mode network in bipartite networks

Projection is a widely used method in bipartite networks. However, each projection has a specific application scenario and differs in the forms of mapping for bipartite networks. In this paper, inspired by the network-based information exchange dynamics, we propose a uniform framework of projection. Subsequently, an information exchange rate projection based on the nature of community structures of a network （named IERCP） is designed to detect community structures of bipartite networks. Results from the synthetic and real-world networks show that the IERCP algorithm has higher performance compared with the other projection methods. It suggests that the IERCP may extract more information hidden in bipartite networks and minimize information loss.

Cluster projective synchronization of complex networks with nonidentical dynamical nodes

We investigate a new cluster projective synchronization （CPS） scheme in time-varying delay coupled complex dynamical networks with nonidentical nodes. Based on the community structure of the networks, the controllers are designed differently for the nodes in one community, which have direct connections to the nodes in the other communities and the nodes without direct connections to the nodes in the other communities. Some sufficient criteria are derived to ensure the nodes in the same group projectively synchronize and there is also projective synchronization between nodes in different groups. Particularly, the weight configuration matrix is not assumed to be symmetric or irreducible. The numerical simulations are performed to verify the effectiveness of the theoretical results.

RECURRENT NEURAL NETWORK MODEL BASED ON PROJECTIVE OPERATOR AND ITS APPLICATION TO OPTIMIZATION PROBLEMS

The recurrent neural network （RNN） model based on projective operator was studied. Different from the former study, the value region of projective operator in the neural network in this paper is a general closed convex subset of n-dimensional Euclidean space and it is not a compact convex set in general, that is, the value region of projective operator is probably unbounded. It was proved that the network has a global solution and its solution trajectory converges to some equilibrium set whenever objective function satisfies some conditions. After that, the model was applied to continuously differentiable optimization and nonlinear or implicit complementarity problems. In addition, simulation experiments confirm the efficiency of the RNN.

Projective synchronization of spatiotemporal chaos in a weighted complex network

Projective synchronization of a weighted complex network is studied in which nodes are spatiotemporal chaos systems and all nodes are coupled not with the nonlinear terms of the system but through a weighted connection. The range of the linear coefficient matrix of separated configuration, when the synchronization is implemented, is determined according to Lyapunov stability theory. It is found that projective synchronization can be realized for unidirectional star-connection even if the coupling strength between the nodes is a given arbitrary weight value. The Gray-Scott models having spatiotemporal Chaos behaviours are taken as nodes in the weighted complex network, and simulation results of spatiotemporal synchronization show the effectiveness of the method.