Applied Mechanics and Materials
Vol. 307
Vol. 307
Applied Mechanics and Materials
Vols. 303-306
Vols. 303-306
Applied Mechanics and Materials
Vol. 302
Vol. 302
Applied Mechanics and Materials
Vols. 300-301
Vols. 300-301
Applied Mechanics and Materials
Vol. 299
Vol. 299
Applied Mechanics and Materials
Vols. 295-298
Vols. 295-298
Applied Mechanics and Materials
Vols. 291-294
Vols. 291-294
Applied Mechanics and Materials
Vol. 290
Vol. 290
Applied Mechanics and Materials
Vol. 289
Vol. 289
Applied Mechanics and Materials
Vol. 288
Vol. 288
Applied Mechanics and Materials
Vols. 284-287
Vols. 284-287
Applied Mechanics and Materials
Vol. 283
Vol. 283
Applied Mechanics and Materials
Vol. 282
Vol. 282
Applied Mechanics and Materials Vols. 291-294
Paper Title Page
Abstract: In the "sustainable development" under the influence of ethics, professional colleges and universities Electricity experiments and the campus network are facing new opportunities and challenges. This paper that presents experimental and universities should carry out green building green campus, discusses in detail the power class of "green experiment" and college "green network" of the specific content of the power class that should focus on the development of laboratory simulation experiments, virtual experiments, the network test and saving experiment, so we can build an energy-based, health-based, harmony-based network software and hardware environment in the "green network"; green experiments and the specific implementation method about green network had been launched a more in-depth discussion and analysis which are a kinds of colleges and universities and networking power quasi-experimental values of the new goals and explore.
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Abstract: Many methods thus have been proposed to predict traffic conditions. However, it is difficult to accurately predict traffic jam, because it requires a wide range of knowledge such as statistics and informational technology. It is known that the probability of traffic jam can be evaluated by travel times of passing cars in a location of the motorway. In this paper, we restrict our attention to finding more efficient statistical methods through comparing models. For this reason, we used Multidimensional Scaling statistical methods to study the relationship between traffic conditions and travel time in different locations and times. This work aims at applying basic models to forecast traffic conditions.
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