A review of artificial intelligence-based optimization techniques for the sizing of integrated renewable energy systems in smart cities

We design and implement an intelligent IoT-based motion monitoring system to realize the monitoring of three important parameters, namely, the type of movement, the number of movements, and the period of movement in physical activities, and optimize the system to support the simultaneous use by multiple users. Considering the motion monitoring scenario for smart fit, the framework of an IoT-based motion monitoring system is proposed. The framework contains components such as active acquisition nodes, wireless access points, data processing servers, and terminals. In terms of algorithm optimization, research related to active pattern recognition and periodic calculation methods is conducted. For active pattern recognition, two types of classification algorithms with different complexity are proposed based on Support Vector Machine (SVM) and deep neural networks, respectively, to adapt to scenarios with different computational capabilities. For period calculation, a method based on over-zero detection and wavelet transform is proposed to count the number of actions and calculate the period of each action. In 100 times action cycle calculation experiments, the count statistic calculation method achieves 100% calculation accuracy and the active cycle calculation results are close to the real value, which proves the effectiveness of the cycle calculation method. The system provides a multiuser-oriented communication method and realizes accurate and reliable human movement monitoring, which has a wide application prospect in the fields of physical education and rehabilitation training.

Section: Movement Intelligent Monitoring System Optimizationmentioning

confidence: 99%

[Retracted] Optimization of IoT‐Based Motion Intelligence Monitoring System

Qiao¹,

Zhang

Chen

2021

“…Reliability refers to the degree of consistency of the results obtained when the same method is used to measure the same object repeatedly, in this case, the reliability of the scale data. When the measurement object is repeatedly measured, the systematic error does not affect the measured results, but mainly the influence of random error causes the reliability to decrease [20][21][22][23][24]. Only when the measurement results are consistent with the true value or very small difference, the reliability of the measured results is high, to ensure the authenticity and reliability of the scale and avoid the impact on the analysis results, so the scale needs to be tested for reliability.…”

Section: Complexitymentioning

confidence: 99%

[Retracted] Application of Computer Simulation Optimization Algorithm in Waste Treatment of Drilling Engineering

Shu

Zhang²

2021

The existing computer technology is used to conduct an in-depth study and analysis of drilling waste treatment, and the results are analyzed by computer simulation optimization algorithms. Based on the system theory, we define the research system, combine the unique characteristics of the technological innovation mechanism of drilling waste treatment, and use the internal and external factors affecting the technological innovation dynamics of drilling waste treatment, such as drilling waste treatment capacity, from the current actual situation. On this basis, factor analysis is used to analyze the factors affecting technological innovation dynamics from both internal and external aspects of the system, establish a system model of technological innovation dynamics of drilling waste disposal, and give the initial values of the simulation model. This will reduce the pollution of the environment and enhance the competitiveness of enterprises. Drilling waste treatment technology is getting increased attention, but at this stage, there is no suitable technology innovation mechanism for drilling waste treatment. Through the simulation trend chart obtained by sensitivity analysis, the key factors in the system are found, and the innovation power mechanism of drilling waste treatment technology is constructed, which provides a basis for the formulation of enterprise technological innovation strategies and the development of technological innovation activities. Research on the dynamic mechanism of drilling waste treatment technology innovation explores a waste treatment mechanism suitable for the drilling industry, so as to promote the steady development of the drilling industry and at the same time provide theoretical support for the treatment of drilling engineering waste.

“…rough the above analysis, although both the DTW algorithm and the string alignment algorithm are based on dynamic programming algorithms, the time complexity of the string alignment algorithm is much lower than that of the DTW algorithm under the same conditions, which is the biggest advantage of the cozy note string alignment algorithm. e string alignment algorithm also has an artificially caused disadvantage, because the string alignment algorithm is based on note features, but the extraction of the note features itself introduces human error, which leads to a decrease in the retrieval accuracy of the algorithm [26][27][28].…”

Section: Subsequence Music Retrieval Algorithm Modelmentioning

confidence: 99%

[Retracted] Matching Subsequence Music Retrieval in a Software Integration Environment

Qin

2021

This paper firstly introduces the basic knowledge of music, proposes the detailed design of a music retrieval system based on the knowledge of music, and analyzes the feature extraction algorithm and matching algorithm by using the features of music. Feature extraction of audio data is the important research of this paper. In this paper, the main melody features, MFCC features, GFCC features, and rhythm features, are extracted from audio data and a feature fusion algorithm is proposed to achieve the fusion of GFCC features and rhythm features to form new features under the processing of principal component analysis (PCA) dimensionality reduction. After learning the main melody features, MFCC features, GFCC features, and rhythm features, based on the property that PCA dimensionality reduction can effectively reduce noise and improve retrieval efficiency, this paper proposes vector fusion by dimensionality reduction of GFCC features and rhythm features. The matching retrieval of audio features is an important task in music retrieval. In this paper, the DTW algorithm is chosen as the main algorithm for retrieving music. The classification retrieval of music is also achieved by the K-nearest neighbor algorithm. In this paper, after implementing the research and improvement of algorithms, these algorithms are integrated into the system to achieve audio preprocessing, feature extraction, feature postprocessing, and matching retrieval. This article uses 100 different kinds of MP3 format music as the music library and randomly selects 4 pieces each time, and it tests the system under different system parameters, recording duration, and environmental noise. Through the research of this paper, the efficiency of music retrieval is improved and theoretical support is provided for the design of music retrieval software integration system.