EXCEL 发表于 2025-3-25 04:54:01
The Possibilities of Scientific Explanationjectives are solved using known optimization techniques. Previously mentioned process analysis information is gathered through the Internet of Things (IoT); finally, the test results are analyzed and contrasted with other existing optimization techniques.灿烂 发表于 2025-3-25 07:50:38
http://reply.papertrans.cn/17/1622/162117/162117_22.pngELUC 发表于 2025-3-25 14:16:49
The Reason Ability of the Deductive Model,e simulation outcome depicts that the presented approach obtained maximum accuracy. Moreover, comparative analysis implied that the neuro-fuzzy model performs better when compared with alternate techniques.exquisite 发表于 2025-3-25 19:32:20
Probabilities in Branching Structures recognize the characters in real time. The RTLPR-CNN model undergoes extensive validation on the HumAIn 2019 dataset. A detailed qualitative and quantitative analysis is conducted and the simulation results indicated the effective performance of the RTLPR-CNN model compared to existing LPR models in a significant manner.啪心儿跳动 发表于 2025-3-25 23:59:17
An Intelligent Classification Model for Big Data with Artificial Intelligence in Social Internet ofthe presented EHO-RBF model on a set of four benchmark datasets. The experimental outcome stated that the presented EHO-RBF model attained maximum accuracy values of 98.8, 98.6, 98.4, and 98.5 for the datasets I–IV, respectively.deadlock 发表于 2025-3-26 03:20:03
http://reply.papertrans.cn/17/1622/162117/162117_26.png思想灵活 发表于 2025-3-26 08:02:29
http://reply.papertrans.cn/17/1622/162117/162117_27.pngHarbor 发表于 2025-3-26 08:39:20
Intelligent Heart Disease Detection and Classification Method Using Optimal Neuro-Fuzzy with Stochae simulation outcome depicts that the presented approach obtained maximum accuracy. Moreover, comparative analysis implied that the neuro-fuzzy model performs better when compared with alternate techniques.秘方药 发表于 2025-3-26 13:04:14
http://reply.papertrans.cn/17/1622/162117/162117_29.png碌碌之人 发表于 2025-3-26 20:07:53
The Possibilities of Scientific Explanationnce techniques to implement the smart water monitoring system. The proposed work utilized Raspberry Pi and low-cost sensors to monitor water resources. The output of the research system is found to be better compared to existing systems.