AIMC Topic: Algorithms

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Dam deformation forecasting using SVM-DEGWO algorithm based on phase space reconstruction.

PloS one
A hybrid model integrating chaos theory, support vector machine (SVM) and the difference evolution grey wolf optimization (DEGWO) algorithm is developed to analyze and predict dam deformation. Firstly, the chaotic characteristics of the dam deformati...

AcneGrader: An ensemble pruning of the deep learning base models to grade acne.

Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)
BACKGROUND: Acne is one of the most common skin lesions in adolescents. Some severe or inflammatory acne leads to scars, which may have major impacts on patients' quality of life or even job prospects. Grading acne plays an important role in diagnosi...

Benchmarking Object Detection Deep Learning Models in Embedded Devices.

Sensors (Basel, Switzerland)
Object detection is an essential capability for performing complex tasks in robotic applications. Today, deep learning (DL) approaches are the basis of state-of-the-art solutions in computer vision, where they provide very high accuracy albeit with h...

Multi-Swarm Algorithm for Extreme Learning Machine Optimization.

Sensors (Basel, Switzerland)
There are many machine learning approaches available and commonly used today, however, the extreme learning machine is appraised as one of the fastest and, additionally, relatively efficient models. Its main benefit is that it is very fast, which mak...

Deep Learning for Joint Pilot Design and Channel Estimation in MIMO-OFDM Systems.

Sensors (Basel, Switzerland)
In MIMO-OFDM systems, pilot design and estimation algorithm jointly determine the reliability and effectiveness of pilot-based channel estimation methods. In order to improve the channel estimation accuracy with less pilot overhead, a deep learning s...

Application of Fuzzy Clustering Model in the Classification of Sports Training Movements.

Computational intelligence and neuroscience
In order to accurately analyze the movements of sports training using artificial intelligence techniques, an improved fuzzy clustering model is proposed in this study. The fuzzy C-means is used to granulate the multilabel space, and the correlation d...

Commercial Bank Credit Grading Model Using Genetic Optimization Neural Network and Cluster Analysis.

Computational intelligence and neuroscience
Commercial banks are facing unprecedented credit risk challenges as the financial market becomes more volatile. Based on this, this study proposes and builds a credit risk assessment model for commercial banks based on GANN from the standpoint of com...

Neural Network Technology-Based Optimization Framework of Financial and Management Accounting Model.

Computational intelligence and neuroscience
Traditional financial accounting has gradually evolved into management accounting in order to adapt to changing times and developments. To avoid being obliterated by the times, accountants must gradually improve their professional and comprehensive a...

Characteristic Analysis and Route Optimization of Heterogeneous Neural Network in Logistics Allocation System.

Computational intelligence and neuroscience
Logistics distribution vehicle scheduling plays an important role in the supply chain. With the wide application of e-commerce technology and the increasing diversification of urban industrial and commercial development mode, the optimal scheduling o...

The Influence of Artificial Intelligence on Visual Elements of Web Page Design under Machine Vision.

Computational intelligence and neuroscience
As the presentation form of the web, web pages contain a lot of important information in web design. As many information carriers, such as sound, graphics, and text, web pages have been integrated and have played a good role in visual transmission. I...