Development and selection in adaptive evolution
ثبت نشده
چکیده
and βSI/N, with I, S and N representing numbers will not model mass action. The issue of estimating local population density is indeed not trivial [4]. However, all standard transect-, quadrator linebased population estimation methods (and most indices) return an estimate of local population density, rather than of population size. Mark–recapture methods aim to estimate population size, but measure local density unless applied to a spatially constrained population. The real issue, which we discussed at length, is determining the appropriate ‘local’ scale on which transmission occurs, and how variation in local density can cause transmission to differ from what might be predicted from mean population density over a larger area. De Jong et al. suggest that most of the variant transmission models that we describe are empirical, but mechanistic derivations have been proposed. These largely involve spatial patchiness of disease, leading to a transmission term using ‘mean crowding’rather than mean density [5]. This is the mean field approximation to a spatially heterogeneous process, and leads directly to other approximations, such as the negative binomial, as discussed in Ref. [1]. The approximations are equally appropriate for any heterogeneity in risk of infection between individuals [6]. Because of this mechanistic link, we prefer the term ‘phenomenological’to ‘empirical’; the models have a functional form that is intended to represent more complex processes. One of our main conclusions was that spatially explicit mechanistic models of the transmission process and of the contact structures are required. However, simple models that represent transmission with a few parameters will continue to be necessary and the correspondence between the two is an important area for future investigation.
منابع مشابه
A Differential Evolution and Spatial Distribution based Local Search for Training Fuzzy Wavelet Neural Network
Abstract Many parameter-tuning algorithms have been proposed for training Fuzzy Wavelet Neural Networks (FWNNs). Absence of appropriate structure, convergence to local optima and low speed in learning algorithms are deficiencies of FWNNs in previous studies. In this paper, a Memetic Algorithm (MA) is introduced to train FWNN for addressing aforementioned learning lacks. Differential Evolution...
متن کاملInvestigating and Analysing Instructional Design and Workplace Learning Models and Selection of Adaptive Model to Optimize Organizational Training in Petrochemical Industry
The present research aimed to analyze instructional design,workplace learning, and selecting the optimum model of learning for human resources training in petrochemical industry.The previous roles have become faint and new opportunities have appeared in petrochemical industry by starting the process of privatization and changing the nature of the company from holding to a governance and develop...
متن کاملOn Feasibility of Adaptive Level Hardware Evolution for Emergent Fault Tolerant Communication
A permanent physical fault in communication lines usually leads to a failure. The feasibility of evolution of a self organized communication is studied in this paper to defeat this problem. In this case a communication protocol may emerge between blocks and also can adapt itself to environmental changes like physical faults and defects. In spite of faults, blocks may continue to function since ...
متن کاملTuning of Extended Kalman Filter using Self-adaptive Differential Evolution Algorithm for Sensorless Permanent Magnet Synchronous Motor Drive
In this paper, a novel method based on a combination of Extended Kalman Filter (EKF) with Self-adaptive Differential Evolution (SaDE) algorithm to estimate rotor position, speed and machine states for a Permanent Magnet Synchronous Motor (PMSM) is proposed. In the proposed method, as a first step SaDE algorithm is used to tune the noise covariance matrices of state noise and measurement noise i...
متن کاملDeveloping Adaptive Differential Evolution as a New Evolutionary Algorithm, Application in Optimization of Chemical Processes
متن کامل
A model of developmental evolution: selection, pleiotropy and compensation.
Development and physiology translate genetic variation into phenotypic variation and determine the genotype-phenotype map, such as which gene affects which character (pleiotropy). Any genetic change in this mapping reflects a change in development. Here, we discuss evidence for variation in pleiotropy and propose the selection, pleiotropy and compensation model (SPC) for adaptive evolution. It ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2002