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Titlebook: Software Architectures for Product Families; International Worksh Frank Linden Conference proceedings 2000 Springer-Verlag Berlin Heidelber

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51#
發(fā)表于 2025-3-30 12:02:41 | 只看該作者
52#
發(fā)表于 2025-3-30 15:50:20 | 只看該作者
53#
發(fā)表于 2025-3-30 16:37:05 | 只看該作者
54#
發(fā)表于 2025-3-30 23:16:19 | 只看該作者
Jan Bosch conditions viz. methanol to oil molar ratio (6:1), catalyst amount (1?wt.?%), reaction temperature (60?°C), and reaction time (15?min) for biodiesel production (98.1% yield) using hydrodynamic cavitation technique. They used a method of varying one factor at a time while the other three factors wer
55#
發(fā)表于 2025-3-31 02:55:41 | 只看該作者
Tuomo Vehkom?ki,Kari K?ns?l?rithms. The comparison is made in terms of accuracy assessment and quality analysis (visual analysis) of the obtained classified image. It showed that our proposed approach outperformed the other conventional classifiers in terms of qualitative analysis and has higher cross-validation accuracy than
56#
發(fā)表于 2025-3-31 07:53:27 | 只看該作者
Mikael Svahnberg,Jan Boschthen artificial neural networks. Primarily four types of network architectures in deep learning are identified and discussed in this work. They are unsupervised pre-trained network, convolution neural network, recurrent neural network and recursive neural network architectures. Types and availabilit
57#
發(fā)表于 2025-3-31 09:45:35 | 只看該作者
Rodrigo Cerón,Juan C. Due?as,Juan A. de la Puenterithms. The comparison is made in terms of accuracy assessment and quality analysis (visual analysis) of the obtained classified image. It showed that our proposed approach outperformed the other conventional classifiers in terms of qualitative analysis and has higher cross-validation accuracy than
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