adhesive
发表于 2025-3-30 08:26:23
http://reply.papertrans.cn/11/1004/100342/100342_51.png
悦耳
发表于 2025-3-30 14:08:56
https://doi.org/10.1007/978-3-658-42323-0emming from incomplete theoretical knowledge and experimental data. Often, fuzzy logic and soft-computing-based approaches are used to deal with this complexity. However, works devoted to account for both fuzziness and partial reliability of information in material selection are scarce. To account f
杀子女者
发表于 2025-3-30 18:28:59
https://doi.org/10.1007/978-3-658-42700-9ane reversal. The relevance of research is postulated by significant damage caused by disasters to ecology, life, health, economy etc. In this work, we tackle fuzzy transportation with transit parameters of arc capacities and traversal time arguments to produce actual evacuation in dynamic condition
Affirm
发表于 2025-3-30 23:21:27
http://reply.papertrans.cn/11/1004/100342/100342_54.png
BILIO
发表于 2025-3-31 03:32:46
http://reply.papertrans.cn/11/1004/100342/100342_55.png
鄙视
发表于 2025-3-31 06:35:08
http://reply.papertrans.cn/11/1004/100342/100342_56.png
Spongy-Bone
发表于 2025-3-31 10:28:48
Methodologie und Auswertungsverfahren,r plugging point (CFPP) of different types of biodiesel. Moreover, the accuracy of the proposed models is compared with the Quadratic model (QM), and Multiple Linear Regression (MLR). For this aim, estimating monounsaturated (MUFAMEs), polyunsaturated (PUFAMEs), and saturated (SFAMEs), the degree of
孵卵器
发表于 2025-3-31 14:46:14
http://reply.papertrans.cn/11/1004/100342/100342_58.png
危机
发表于 2025-3-31 19:23:46
Sebastian Oetzel,Andreas Luppold limited quota. In the process of determining scholarship, we use the criteria which evaluated subjectively and some students who have the ability or value that is not so different. In this case, the application of fuzzy logic theory is an effective tool. Thus, fuzzy logic allows to describe the kno
dragon
发表于 2025-4-1 01:09:48
https://doi.org/10.1007/978-3-658-42890-7Computed tomography (CT) imaging is preferred for imaging kidney stone disease. This study aims to compare the accuracy capabilities of deep learning models in classifying abdominal CT images. In this paper, we examine the use of pre-trained deep learning models to distinguish between patients with