Titlebook: Computational Intelligence Methods for Green Technology and Sustainable Development; Proceedings of the I Yo-Ping Huang,Wen-June Wang,Nguye

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Proposed Novel Fish Freshness Classification Using Effective Low-Cost Threshold-Based and Neural Netherefore highly attracted by the research and industry community. This paper proposes novel fish freshness classification models based on threshold-based and neural network-based approaches on extracted image features. These features are identified based on physiological characteristics of fish eyes

Parallel

上流社會(huì)

Malware Classification by Using Deep Learning Frameworktechniques are becoming popular for classifying malware. However, most of the existing machine learning methods for malware classifying use shallow learning algorithms such as Support Vector Machine, decision trees, Random Forest, and Naive Bayes. Recently, a deep learning approach has shown superio

MULTI

Attention Mechanism for Fashion Image Captioningy, with the help from rapid development of deep learning, image captioning has become an active research. The encoder-decoder architecture is commonly considered as the baseline method to address image captioning. This model focuses on recognizing objects and the relationship among these objects. Ho

paleolithic

Microgram

規(guī)范就好

Designing and Analysis of a Soft Robotic Arm design can cope with some existing limitations of the Robot for Interactive Body Assistance (RIBA) with a lifting capacity of 61 kgs and a limited degree of freedom. The proposed robotic arm is modelled in the computer-aided modelling (CAD) software, namely, SolidWorks. The results show that the de

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ROV Stabilization Using an Adaptive Nonlinear Feedback Controllerially for navy and marine industries. They are highly nonlinear systems and often operate in an unpredictable nature of the ocean environment. Therefore they have many initially uncertain and varying parameters. To overcome this problem, we need controllers adapting itself to such changing condition

落葉劑

On Robust Control of Permanent Magnet Synchronous Generators Using Robust Integral of Error Sign The cascade control structure was established in the PMSG model to be decoupled into two sub-systems. Controllers are designed base on the RISE method for both the inner and outer loop to estimate and cancel uncertainties and disturbances. The stability, tracking effectiveness of the closed system

一美元

A Flexible Sliding Mode Controller for Robot Manipulators Using a New Type of Neural-Network Predictrk design. The total dynamics of the robot is first estimated by the neural network in which a new type of learning laws is proposed based on twisting excitation signals. A flexible sliding mode control interface is then developed to realize control objectives using the estimation result of the neur