Maintaining behavior change is one of the major challenges in weight management and long-term weight loss. We investigated the impact of the cognitive complexity of eating rules on adherence to weight management programs. We studied whether popular weight management programs can fail if participants find the rules too complicated from a cognitive perspective, meaning that individuals are not ab...

Memory systems should be plastic to allow for learning; however, they should also retain earlier memories. Here we explore how synaptic weights and memories are retained in models of single neurons and networks equipped with spike-timing-dependent plasticity. We show that for single neuron models, the precise learning rule has a strong effect on the memory retention time. In particular, a soft-...

In evidence theory, conflicting and fuzzy have a significant impact on the results of combination. Nevertheless, existing weight assignment methods can hardly reflect influence combination results. this paper, we address issue by proposing new method for assigning weights corresponding rule. The proposed strengthens consideration evidence. We further incorporate Wasserstein distance to compute ...

Problem statement: Fusion weight tuning based on score reliability is imperative in order to ensure the performances of multibiometric systems are sustained. Approach: In this study, two variant of conditions i.e., different performances of individual subsystems and inconsistent quality of test samples are experimented to multibiometric systems. By applying multialgorithm scheme, two types of f...

FuNe I Adaptive Feedback Controller (FuNe I AFC) has been successfully implemented as a regulator controller. The design of FuNe I AFC is independent of plant dynamics and it is online adaptive. The adaptive feature of this controller is the result of a Weight Matrix updated by rule based reinforcement learning. The Weight Matrix updates the connection weights between rule nodes and the output ...

This paper presents a novel boosting algorithm for genetic learning of fuzzy classification rules. The method is based on the iterative rule learning approach to fuzzy rule base system design. The fuzzy rule base is generated in an incremental fashion, in that the evolutionary algorithm optimizes one fuzzy classifier rule at a time. The boosting mechanism reduces the weight of those training in...

The weight perturbation learning was proposed as a learning rule which adds perturbation to the variable parameters of learning machines. Generalization performance of the weight perturbation learning was analyzed by statistical mechanical methods. The weight perturbation learning has the same asymptotic generalization property as the Perceptron learning. In this paper we consider difference be...

Association rule mainly focuses on large transactional databases. In association rule mining all items are considered with equal weightage. But it is not suitable for all datasets. The weight should be considered based on the importance of the item. In our previous work HITS algorithm (Hyperlink Induced Topic Search) is used to find the weight of an item w-support is calculated for generating f...

In this paper, a new class of a weighted quadrature rule is represented as --------------------------------------------  where  is a weight function,  are interpolation nodes,  are the corresponding weight coefficients and denotes the error term. The general form of interpolation nodes are considered as   that  and we obtain the explicit expressions of the coefficients  using the q-...