نتایج جستجو برای: nearest neighbors knn algorithm four artificial neural network models and two hammerstein
تعداد نتایج: 17360759 فیلتر نتایج به سال:
correct estimation of suspended sediment transported by a river is an important practice in water structure design, environmental problems and water quality issues. conventionally, sediment rating curve used for suspended sediment estimation in rivers. in this method discharge and sediment discharge or concentration related using regression relation that generally is exponential model. respect ...
We address the problem of k Nearest Neighbor (kNN) search in networks using a random walk based proximity measure. Our approach retrieves the exact top neighbors at query time without relying on off-line indexing or summaries of the entire network. This makes it suitable for very large networks, as well as for composite network overlays mixed at query time. We provide scalability and flexibilit...
In this paper, we present a novel non-parametric clustering technique, which is based on an iterative algorithm that peels off layers of points around the clusters. Our technique is based on the notion that each latent cluster is comprised of layers that surround its core, where the external layers, or border points, implicitly separate the clusters. Analyzing the K-nearest neighbors of the poi...
background: the purpose of this investigation was to compare empirically predictive ability of an artificial neural network with a logistic regression in prediction of low back pain. methods: data from the second national health survey were considered in this investigation. this data includes the information of low back pain and its associated risk factors among iranian people aged 15 years a...
drought is random and nonlinear phenomenon and using linear stochastic models, nonlinear artificial neural network and hybrid models is advantaged for drought forecasting. this paper presents the performances of autoregressive integrated moving average (arima), direct multi-step neural network (dmsnn), recursive multi-step neural network (rmsnn), hybrid stochastic neural network of directive ap...
data envelopment analysis (dea) is a powerful tool for measuring relative efficiency of organizational units referred to as decision making units (dmus). in most cases dmus have network structures with internal linking activities. traditional dea models, however, consider dmus as black boxes with no regard to their linking activities and therefore do not provide decision makers with the reasons...
Since the development of surface water control needs accurate access to flow behavior of sediment rates, the lack of sediment measurement stations, the novelty of most stations and the lack of statistics on the deposit make it difficult to properly evaluate and simulate the flow behavior and their sediments. In a watershed, the morphological characteristics and sediment load of flow affect each...
Today, the global positioning systems (GPS) do not work well in buildings and in dense urban areas when there is no lines of sight between the user and their satellites. Hence, the local positioning system (LPS) has been considerably used in recent years. The main purpose of this research is to provide a four-layer artificial neural network based on nonlinear system solver (NLANN) for local pos...
Recently, increasing population rate and urbanization growth, made the significance of land use more to double; So that the plan of land use in the cities has been encountered with vast imposed changes. In order to represent those changes, this study aims to model the land use changes, as an example in Khorramabad city, Lorstan province, Iran. In this regard, the raw Satellite images which capt...
In this research, a novel computational intelligencebased algorithm to detect artifacts, specifically arrows, in medical images is presented. Image analyses techniques are developed to find the symbols and text automatically. Features are computed from the shape of arrow for the discrimination of arrows from other artifacts. We investigate a biologically-inspired reinforcement learning (RL) app...
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