an alumina supported co/ni catalyst was prepared by sol-gel procedure to study the catalytic behavior during fischer-tropsch synthesis in a fixed-bed reactor. the effect of co conversion (10-50%) on hydrocarbon product distribution (ch4, c5+ and c2-c4 olefin selectivities) was studied. selectivity for ch4 decreased, while those of c5+ and olefin selectivities increased with increasing co conver...

For winning in global competition, companies need to recognition and monitoring of customer's behavior to forecast their behavior and desires earlier than competitors. This research tries to recognize the attributes which lead to customer churn. For this, behavior of 3150 subscribers of an Iranian mobile operator, has observed during one year and trends of them has analyzed by a customized LLNF...

In this paper the improvement of the established training algorithm HILOMOT is presented. HILOMOT is a hierarchical tree-construction method based on the ideas of neuronal networks and fuzzy-systems and an advancement of the wellknown LOLIMOT-Algorithm. During the training the input space is divided into subregions with the help of validity functions. This is done iteratively by splitting the c...

The walking beam furnace (WBF) is one of the most prominent process plants often met in an alloy steel production factory and characterised by high non-linearity, strong coupling, time delay, large time-constant and time variation in its parameter set and structure. From another viewpoint, the WBF is a distributed-parameter process in which the distribution of temperature is not uniform. Hence,...

This paper presents a prediction model based on a new neuro-fuzzy algorithm for estimating time in construction projects. The output of the proposed prediction model, which is employed based on a locally linear neuro-fuzzy (LLNF) model, is useful for assessing a project status at different time horizons. Being trained by a locally linear model tree (LOLIMOT) learning algorithm, the model is int...

Almost every real process exhibits nonlinear behavior in a full operating range. Local Model Networks are networks which are composed of locally accurate models, where output is interpolated by smooth locally active validity functions. This divide-and-conquer strategy is a general way of coping with complex systems. The architecture of LMN benefits from being able to incorporate a priori knowle...

An alumina supported Co/Ni catalyst was prepared by sol-gel procedure to study the catalytic behavior during Fischer-Tropsch synthesis in a fixed-bed reactor. The effect of CO conversion (10-50%) on hydrocarbon product distribution (CH4, C5+ and C2-C4 olefin selectivities) was studied. Selectivity for CH4 decreased, while those of C5+<...

The rising complexity of modern automotive engines with an increasing number of actuators and sensors to minimise emissions and fuel consumption and to maximise engine driveability require a detailed supervision for fault detection and on-board diagnosis. The European Community Directive 98/69/EC requires on-board diagnosis for spark ignition engines and will require it for diesel engines as of...

This paper presents a prediction model based on a new neuro-fuzzy algorithm for estimating time in construction projects. The output of the proposed prediction model, which is employed based on a locally linear neuro-fuzzy (LLNF) model, is useful for assessing a project status at different time horizons. Being trained by a locally linear model tree (LOLIMOT) learning algorithm, the model is int...