The accurate classification of reservoir recovery factor is dampened by irregularities such as noisy and high-dimensional features associated with the measurements or characterization. These irregularities, especially a larger number features, make it difficult to perform factor, generated are usually heterogeneous. Consequently, imperative select relevant while preserving amplifying accuracy. ...

For the multi-objective design of heat sinks, several evolutionary algorithms usually require many iterations to converge, which is computationally expensive. Variable-fidelity (VFO) methods were suggested improve efficiency algorithms. However, problems are seldom optimized using VFO. Therefore, a variable-fidelity method (VFMEM) was suggested. Similar other algorithms, VFMEM solves high-fidel...

Regression testing is carried out to test the updated supply code within constraints of time and sources. Since it very difficult run all source every time, case prioritization needed decrease fee regression testing. Various methodologies including extensions white box black prioritization, have been presented considering instances. In this context, employment particle swarm optimization (PSO) ...

This study demonstrates how to use grid-connected hybrid PV and biogas energy with a SMES-PHES storage system in nation frequent grid outages. The primary goal of this work is enhance the HRES’s capacity favorably influence economic viability, reliability, environmental impact. net present cost (NPC), greenhouse gas (GHG) emissions, likelihood power outage are among variables that examined. A m...

in this paper the problem of minimizing the total transmitting power subject to a fixedtotal bit rate in ofdm systems is considered. upper bounds on transmitting power and bit rate ofeach subcarrier can also be taken into account. in practice, the number of bits of each subcarriershould be integer and nonnegative. in this paper an analytical optimal solution is derived for thecase of assuming t...

Hidden Markov Model is a popular statisical method that is used in continious and discrete speech recognition. The probability density function of observation vectors in each state is estimated with discrete density or continious density modeling. The performance (in correct word recognition rate) of continious density is higher than discrete density HMM, but its computation complexity is very ...

Prediction and parameter optimization are effective methods for mine personnel to control blast-induced ground vibration. However, the challenge of prediction lies in multi-factor multi-effect nature open-pit blasting. This study proposes a hybrid intelligent model predict vibrations using least-squares support vector machine (LSSVM) optimized by particle swarm algorithm (PSO). Meanwhile, multi...