We describe our initial attempts to reconcile powerful neural network learning rules derived from computational principles with learning rules derived “bottom-up” from biophysical mechanisms. Using a biophysical model of synaptic plasticity (Shouval, Bear, and Cooper, 2002), we generated numerical synaptic learning rules and compared them to the performance of a Hebbian learning rule in a previ...

runoff estimation is one of the main challenges encountered in water and watershed management. spatial and temporal changes of factors which influence runoff due to het-erogeneity of the basins explain the complicacy of relations. artificial neural network (ann) is one of the intelligence techniques which is flexible and doesn’t call for any much physically complex processes. these networks can...

lithofacies identification can provide qualitative information about rocks. it can also explain rock textures which are importantcomponents for hydrocarbon reservoir description sarvak formation is an important reservoir which is being studied in the marun oilfield, in the dezful embayment (zagros basin). this study establishes quantitative relationships between digital well logs data androutin...

objective(s): chitosan, a biodegradable and cationic polysaccharide with increasing applications in biomedicine, possesses many advantages including mucoadhesivity, biocompatibility, and low-immunogenicity. the aim of this study, was investigating the influence of ph, ratio of azelaic acid/chitosan and molecular weight of chitosan on loading efficiency of azelaic acid in chitosan particles. mat...

this research intends to develop a method based on the artificial neural network (ann) to predict permanent earthquake-induced deformation of the earth dams and embankments. for this purpose, data sets of observations from 152 published case histories on the performance of the earth dams and embankments, during the past earthquakes, was used. in order to predict earthquake-induced deformation o...

this paper deals with volume fraction optimization of functionally graded (fg) beams resting on elastic foundation for maximizing the first natural frequency. the two-constituent functionally graded beam consists of ceramic and metal. these constituents are graded through the thickness of beam according to a generalized power-law distribution. one of the advantages of using generalized power- l...

abstract prediction of input flow into water resources is regarded as one of the most important issues in optimum planning and management in producing electro-water energy and optimum allocation of water into different consumption sources. different parameters affect on input discharge into dams. climate variables including temperature and rainfall have the most effect on input runoff rate to w...

objective(s): a fast and reliable evaluation of the binding energy from a single conformation of a molecular complex is an important practical task. artificial neural networks (anns) are strong tools for predicting nonlinear functions which are used in this paper to predict binding energy. we proposed a structure that obtains binding energy using physicochemical molecular descriptions of the se...