Zobrazeno 1 - 10
of 58
pro vyhledávání: '"Ojha, Varun Kumar"'
Autor:
Ojha, Varun Kumar, Griego, Danielle, Kuliga, Saskia, Bielik, Martin, Bus, Peter, Schaeben, Charlotte, Treyer, Lukas, Standfest, Matthias, Schneider, Sven, Konig, Reinhard, Donath, Dirk, Schmitt, Gerhard
Publikováno v:
Information Sciences 474, 154-169, 2019
This research proposes a framework for signal processing and information fusion of spatial-temporal multi-sensor data pertaining to understanding patterns of humans physiological changes in an urban environment. The framework includes signal frequenc
Externí odkaz:
http://arxiv.org/abs/1812.06128
Publikováno v:
Hybrid Soft Computing Approaches (2015) pp 215-236
Human fatalities are reported due to the excessive proportional presence of hazardous gas components in the manhole, such as Hydrogen Sulfide, Ammonia, Methane, Carbon Dioxide, Nitrogen Oxide, Carbon Monoxide, etc. Hence, predetermination of these ga
Externí odkaz:
http://arxiv.org/abs/1707.01821
The performance of the meta-heuristic algorithms often depends on their parameter settings. Appropriate tuning of the underlying parameters can drastically improve the performance of a meta-heuristic. The Ant Colony Optimization (ACO), a population b
Externí odkaz:
http://arxiv.org/abs/1707.01812
Optimization of neural network (NN) significantly influenced by the transfer function used in its active nodes. It has been observed that the homogeneity in the activation nodes does not provide the best solution. Therefore, the customizable transfer
Externí odkaz:
http://arxiv.org/abs/1707.01810
Publikováno v:
IEEE Transactions on Fuzzy Systems 2017
This paper proposes a design of hierarchical fuzzy inference tree (HFIT). An HFIT produces an optimum treelike structure, i.e., a natural hierarchical structure that accommodates simplicity by combining several low-dimensional fuzzy inference systems
Externí odkaz:
http://arxiv.org/abs/1705.05769
Publikováno v:
Applied Soft Computing, 2017, Volume 52 Pages 909 to 924
Machine learning algorithms are inherently multiobjective in nature, where approximation error minimization and model's complexity simplification are two conflicting objectives. We proposed a multiobjective genetic programming (MOGP) for creating a h
Externí odkaz:
http://arxiv.org/abs/1705.05592
Publikováno v:
Engineering Applications of Artificial Intelligence Volume 60, April 2017, Pages 97 to 116
Over the past two decades, the feedforward neural network (FNN) optimization has been a key interest among the researchers and practitioners of multiple disciplines. The FNN optimization is often viewed from the various perspectives: the optimization
Externí odkaz:
http://arxiv.org/abs/1705.05584
Publikováno v:
International Journal of Nanomedicine 2015,10
Prediction of poly(lactic co glycolic acid) (PLGA) micro- and nanoparticles' dissolution rates plays a significant role in pharmaceutical and medical industries. The prediction of PLGA dissolution rate is crucial for drug manufacturing. Therefore, a
Externí odkaz:
http://arxiv.org/abs/1705.06817
Publikováno v:
Neural Computing and Application, 2016
In this work, a computational intelligence (CI) technique named flexible neural tree (FNT) was developed to predict die filling performance of pharmaceutical granules and to identify significant die filling process variables. FNT resembles feedforwar
Externí odkaz:
http://arxiv.org/abs/1709.04318
Publikováno v:
Neural Comput & Applic (2017) 28: 1343
In this work, we formulated a real-world problem related to sewer pipeline gas detection using the classification-based approaches. The primary goal of this work was to identify the hazardousness of sewer pipeline to offer safe and non-hazardous acce
Externí odkaz:
http://arxiv.org/abs/1707.00561