This paper aims to comprehensively explore the pivotal role of simulation and modeling in the field of Artificial Intelligence (AI). It focuses on elucidating the diverse applications of simulation and modeling in tra...
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This paper aims to comprehensively explore the pivotal role of simulation and modeling in the field of Artificial Intelligence (AI). It focuses on elucidating the diverse applications of simulation and modeling in training AI systems, optimizing algorithms, and enhancing decision-making processes. To achieve this objective, we conducted an extensive review of the literature from the Scopus database, employing a well-defined selection process. We utilized keywords such as "simulation," "modeling," "Artificial Intelligence," and related terms to identify relevant papers published within the last 10 years. The selection criteria included assessing the relevance, quality, contribution, and recent citations of the papers. After a rigorous screening process, we selected 40 papers with the highest overall scores for inclusion in our review. The selected papers encompass a wide range of domains where simulation and modeling play a vital role in advancing AI applications. These domains include manufacturing, healthcare, energy consumption prediction, public sector decision-making, education, environmental modeling, and more. Our review highlights how AI leverages simulation and modeling to improve predictive accuracy, optimize resource allocation, and enhance decision-making processes across diverse sectors. We also discuss the potential future directions in the integration of simulation and modeling with AI, emphasizing its significance in various fields.
This paper presents an optimization of the Rijndael algorithm which can speed up execution on ARM920T *** was selected as the Advanced Encryption Standard (AES) by the National Institute of Standards and Technology (N...
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This paper presents an optimization of the Rijndael algorithm which can speed up execution on ARM920T *** was selected as the Advanced Encryption Standard (AES) by the National Institute of Standards and Technology (NIST).First we present a theoretical analysis of the Rijndael algorithm and code optimization, and then simulation results of the optimized algorithm on ARM920T microprocessor are *** cycles of key schedule for decryption are more than the cycles of key schedule for *** schedule for decryption has larger memory than key schedule for *** (including decryption key schedule) is slower than encryption (including encryption key schedule).The experiment shows the algorithm can be executed on ARM920T microprocessor efficiently.
The course scheduling is a dynamic combination of many factors involved in planning issues, it is to ensure that conflict does not produce a variety of teaching resources, and to meet the requirements of teachers and ...
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The course scheduling is a dynamic combination of many factors involved in planning issues, it is to ensure that conflict does not produce a variety of teaching resources, and to meet the requirements of teachers and classroom resources, in the constraints. The inference engine use the idea of resource allocation, the course arrangement as a reasonable person on demand resource allocation, the use of forward reasoning strategy to optimize the efficiency of the algorithm.
Plant diseases and insect pests have similar symptoms, but it is difficult to distinguish between professional and technical personnel to identify plant diseases and insect pests. In order to accurate extraction of pl...
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Plant diseases and insect pests have similar symptoms, but it is difficult to distinguish between professional and technical personnel to identify plant diseases and insect pests. In order to accurate extraction of plant diseases and insect pests, physiological and pathological characteristics of signal, puts forward a based on lifting wavelet transform feature extraction algorithm optimization scheme, for the study of plant diseases and insect pests damage signal showing the effect of the prior farmers identify any disease, choose the correct method of governance, quickly make the right decision, improve farmers plant diseases and insect pests, harm signal feature extraction and recognition level. The simulation results show that this algorithm can be used to optimize the stability and convergence, and can be used as an ideal plant disease and insect pests signal feature extraction optimizationalgorithm, which can effectively identify the different plant diseases and insect pests.
Based on a large number of literatures and reports, this paper takes communication systems in lifeline engineering as an example, collects as many disaster-related communication data as possible to form a training dat...
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Based on a large number of literatures and reports, this paper takes communication systems in lifeline engineering as an example, collects as many disaster-related communication data as possible to form a training data set, and analyzes the relationship between disaster-related telecommunications data and earthquake intensity. Then, use visual means to preprocess the collected data set. This paper uses different classification algorithms in machine learning, such as Naive Bayes, K-nearest neighbors, logistic regression and support vector machines for classification training of the formed data set. Optimize it, and finally it proposes a reference model that can be used to predict earthquake intensity. Finally, experiments show that the model has good accuracy.
A design methodology to accelerate the face detection for embedded systems is described, starting from algorithm optimization (high level) and ending with software and hardware codesign (low level) by addressing the i...
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ISBN:
(纸本)9781479902255
A design methodology to accelerate the face detection for embedded systems is described, starting from algorithm optimization (high level) and ending with software and hardware codesign (low level) by addressing the issues and the design decisions made at each level based on the performance measurements and system limitations. The implemented embedded face detection system consumes very little power compared with the traditional PC software implementations while maintaining the same detection accuracy. The proposed face detection acceleration methodology is suitable for real time applications.
Weighted frequent pattern mining is suggested to discover more important frequent pattern by considering different weights of each item,and closed frequent pattern mining can reduces the number of frequent patterns an...
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Weighted frequent pattern mining is suggested to discover more important frequent pattern by considering different weights of each item,and closed frequent pattern mining can reduces the number of frequent patterns and keep sufficient result *** this paper,we propose an efficient algorithm DSWFP to mine closed weighted frequent pattern mining over data *** present an efficient algorithm based on sliding window and can discover closed weighted frequent pattern from the recent data.A new efficient DSWFP data structure is used to dynamically maintain the information of transactions and also maintain the closed weighted frequent patterns has been found in the current sliding *** optimization strategies are *** detail of the algorithm DSWFP is also *** studies are performed to evaluate the good effectiveness of DSWFP.
Aiming at the problem of local style migration distortion in image stylization, an improved image style migration algorithm based on deep learning network is proposed. Firstly, the VGGNet-19 network is used to extract...
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Aiming at the problem of local style migration distortion in image stylization, an improved image style migration algorithm based on deep learning network is proposed. Firstly, the VGGNet-19 network is used to extract the convolution layer features of images. Then the characteristics of convolution layer are analyzed, and the combination of style and content features is studied. The Block3 layer with the smallest content loss and style loss is selected for feature fusion with conv1, conv2, conv3, conv4 and conv5 layers. Finally, under the optimal combination of features, Adam algorithm is used to optimize the image style migration. The experimental results show that the proposed algorithm can effectively improve the distortion of local style migration and provide theoretical support for the implementation of style migration technology.
The 2017 Grand Challenge focused on the problem of automatic detection of anomalies for manufacturing equipment. This paper reports the technical details of a solution focused on particular optimizations of the proces...
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ISBN:
(纸本)9781450350655
The 2017 Grand Challenge focused on the problem of automatic detection of anomalies for manufacturing equipment. This paper reports the technical details of a solution focused on particular optimizations of the processing stages. These included customized input parsing, fine tuning of a k-means clustering algorithm and probability analysis using a lazy flavor of a Markov chain. We have observed in our custom implementation that carefully tweaking these processing stages at single node level by leveraging various data stream characteristics can yield good performance results. We start the paper with several observations concerning the input data stream, following with our solution description with details on particular optimizations, and we conclude with evaluation and a discussion of obtained results.
This paper presents a novel algorithm of discrete cosine transform (DCT) for digital theatre system (DTS) and windows media audio (WMA) decoding based on the type IV discrete cosine transform (DCT-IV). By virtue of th...
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ISBN:
(纸本)9781622760350
This paper presents a novel algorithm of discrete cosine transform (DCT) for digital theatre system (DTS) and windows media audio (WMA) decoding based on the type IV discrete cosine transform (DCT-IV). By virtue of the format conversion, the DTS and WMA decoding shares the same DCT-IV kernel, thus increasing the efficiency. The computation of DCT-IV is based on fast Fourier transform (FFT) and the coefficients are calculated in recursive algorithm. The performance of the proposed algorithm is compared with other reported algorithms. Both the efficiency of multiplication computation and the simplicity of hardware implementation are largely improved.
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