Fuzzy clustering methods are conveniently employed in constructing a fuzzy model of a system, but they need to tune some parameters. In this research, FCM is chosen for fuzzy clustering. Parameters such as the number of clusters and the value of fuzzifier significantly influence the extent of generalization of the fuzzy model. These two parameters require tuning to reduce the overfitting in the...

Current architecture complexity requires fine tuning of compiler and runtime parameters to achieve best performance. Autotuning substantially improves default parameters in many scenarios but it is a costly process requiring long iterative evaluations. We propose an automatic piecewise autotuner based on CERE (Codelet Extractor and REplayer). CERE decomposes applications into small pieces calle...

Although many PID tuning approaches are available, it is not easy to find a method that does not require any engineer/operator interference. In this work, we present a fully automated approach for PID tuning based on relay feedback. This method involves sending the relay feedback test data from PLCs (Programmable Logic Controller) into a historian, analyzing the test data using a tuning applica...

Current architecture complexity requires fine tuning of compiler and runtime parameters to achieve full potential performance. Autotuning substantially improves default parameters in many scenarios but it is a costly process requiring a long iterative evaluation. We propose an automatic piecewise autotuner based on CERE (Codelet Extractor and REplayer). CERE decomposes applications into small p...

Performance tuning of Database Management Systems (DBMS) is complex as well as challenging task since it involves identification and alteration of several key performance tuning parameters. The quality of tuning and the extent of performance enhancement achieved greatly depend on the skill and experience of the Database Administrator (DBA). The ability of our automated database design to adapt ...

Automatic performance tuning (auto-tuning) has been used in parallel numerical applications for adapting performance-relevant parameters. We extend auto-tuning to general-purpose parallel applications on multicores. This paper concentrates on Atune-IL, an instrumentation language for specifying a wide range of tunable parameters for a generic auto-tuner. Tunable parameters include the number of...

An experimental and theoretical investigation of the Nigerian slit gong is reported. It is shown that in tuning the gong the artisan ensures that the frequencies of the two lowest mechanical resonances are nearly coincident with the frequencies of two of the acoustic resonances of the internal cavity. Four possible tuning parameters are identified and the effects of changing these parameters ar...

Genetic algorithm (GA) has been used in this study for a new approach of suboptimal model reduction in the Nyquist plane and optimal time domain tuning of proportional-integral-derivative (PID) and fractional-order (FO) PI(λ)D(μ) controllers. Simulation studies show that the new Nyquist-based model reduction technique outperforms the conventional H(2)-norm-based reduced parameter modeling techn...

We examined parameter optimization in JSBACH ecosystem model, applied for two boreal forest sites (Hyytiälä and Sodankylä) in Finland. We identified and tested key parameters in soil hydrology and forest water and carbon exchange related formulations and optimized them using the Adaptive Metropolis algorithm (AM) for Hyytiälä with a five year calibration period (2000–2004) followed by a four ye...

Most multivariate calibration methods require selection of tuning parameters, such as partial least squares (PLS) or the Tikhonov regularization variant ridge regression (RR). Tuning parameter values determine the direction and magnitude of respective model vectors thereby setting the resultant predication abilities of the model vectors. Simultaneously, tuning parameter values establish the cor...