Process simulation is an increasingly useful tool for the analysis of processes in the mineral industry. The ability to simulate process behavior without having to disturb plant operation prevents the loss of man-hours and production. Additionally, simulation tools provide a platform for the development of control and optimization strategies. Model predictive control, in particular, relies heav...

ICE is a new incremental construction algorithm of a hybrid system for continuous learning tasks. The basis of the hybrid system is a radial basis function (RBF) network layer. The second layer consists of local models. The two layers are closely combined with a strong interaction. For example information from the model-layer is used by the RBF-layer to decide if new RBF-neurons are needed and ...

Speciation, the process by which new biological species arise, involves the evolution of reproductive barriers, such as hybrid sterility or inviability between populations. However, identifying hybrid incompatibility genes remains a key obstacle in understanding the molecular basis of reproductive isolation. We devised a genomic screen, which identified a cell cycle-regulation gene as the cause...

Ayurveda is one of the oldest holistic treatment systems in world. Finding an accurate and correct plant key to working Ayurvedic treatment. Identification medicinal plants a tedious job due look-alike feature availability issue with other plants. This paper emphases on ideal identification classification use using deep learning approaches. Previously researchers have used traditional machine t...

Essential hypertension is characterized by chronically elevated blood pressure with no specific underlying medical cause. Data on family history of affected individuals coupled with disease concordance rate in twins has established that both genetic and environmental factors determine susceptibility to hypertension. The heritability of hypertension is often cited in the range of 30% to 60%, wit...

Parameter tuning is an important step in automatic fuzzy model identification from sample data. It aims at the determination of quasi-optimal parameter values for fuzzy inference systems using an adequate search technique. In this paper, we introduce a new hybrid search algorithm that uses a variant of the cross-entropy (CE) method for global search purposes and a hill climbing type approach to...

Hybrid system identification is composed of two subproblems: estimate the discrete state or mode for each data point, and estimate the submodel governing the dynamics of the continuous state for each mode. For linear hybrid systems, the paper proposes to tackle these problems in a single step by simultaneously approximating each submodel while associating data points to each of these. The metho...