نتایج جستجو برای: adaptive multimodal optimization
تعداد نتایج: 533391 فیلتر نتایج به سال:
Recent theoretical research has shown that self-adjusting and self-adaptive mechanisms can provably outperform static settings in evolutionary algorithms for binary search spaces. However, the vast majority of these studies focuses on unimodal functions which do not require algorithm to flip several bits simultaneously make progress. In fact, existing are designed detect local optima have any o...
Evolutionary computation is inspired by nature in order to formulate metaheuristics capable to optimize several kinds of problems. A family of algorithms has emerged based on this idea; e.g. genetic algorithms, evolutionary strategies, particle swarm optimization (PSO), ant colony optimization (ACO), etc. In this paper we show a populationbased metaheuristic inspired on the gravitational forces...
The calibration of complex models of biological systems requires numerical simulation and optimization procedures to infer undetermined parameters and fit measured data. The optimization step typically employs heuristic global optimization algorithms, but due to measurement noise and the many degrees of freedom, it is not guaranteed that the identified single optimum is also the most meaningful...
Many real practical applications are often needed to find more than one optimum solution. Existing Evolutionary Algorithm (EAs) are originally designed to search the unique global value of the objective function. The present work proposed an improved niching based scheme named spatially neighbors best search technique combine with crowding-based differential evolution (SnbDE) for multimodal opt...
Particle swarm optimization (PSO) has received increasing interest from the optimization community due to its simplicity in implementation and its inexpensive computational overhead. However, PSO has premature convergence, especially in complex multimodal functions. Extremal Optimization (EO) is a recently developed local-search heuristic method and has been successfully applied to a wide varie...
The calibration of complex models of biological systems requires numerical simulation and optimization procedures to infer undetermined parameters and fit measured data. The optimization step typically employs heuristic global optimization algorithms, but due to measurement noise and the many degrees of freedom, it is not guaranteed that the identified single optimum is also the most meaningful...
Predicting the end of user input turns in a multimodal system can be complex. User interactions vary across a spectrum from single, unimodal inputs to multimodal combinations delivered either simultaneously or sequentially. Early multimodal systems used a fixed duration temporal threshold to determine how long to wait for the next input before processing and integration. Several recent studies ...
Predicting the end of user input turns in a multimodal system can be complex. User interactions vary across a spectrum from single, unimodal inputs to multimodal combinations delivered either simultaneously or sequentially. Early multimodal systems used a fixed duration temporal threshold to determine how long to wait for the next input before processing and integration. Several recent studies ...
نمودار تعداد نتایج جستجو در هر سال
با کلیک روی نمودار نتایج را به سال انتشار فیلتر کنید