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2018 3rd International Conference on Computational Intelligence and Applications (ICCIA)最新文献

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Optimization of Distribution Route with Vehicle Routing Problem with Transshipment Facilities (VRPTF) 带转运设施车辆路线问题的配送路线优化
R. Syahputra, K. Komarudin, A. R. Destyanto
VRPTF is one of many various kinds of Vehicle Routing Problem (VRP) which is still slightly discussed. As logistic is always an issue for both developed and developing country, this research aims to compare whether or not VRPTF is suitably applied to logistic distribution in Indonesia. As we know, Indonesia is one of the archipelagic countries, so distributing goods across the island requires a high cost. The purpose of this paper is giving cost comparison by using VRPTF method, Hub-and-Spoke method, and Capacitated VRP method, so countries that may experience similar case can apply this method and get the optimize route model. This study was conducted by taking case study from a company that produces a non-perishable product and generate using Open Solver and VBA program, both in Excel. This research indicates that VRPTF method is giving optimize cost than other methods.
VRPTF是各种各样的车辆路由问题(Vehicle Routing Problem, VRP)中的一种,目前对VRP的讨论还很少。由于物流一直是发达国家和发展中国家的问题,本研究旨在比较VRPTF是否适用于印尼的物流配送。正如我们所知,印度尼西亚是一个群岛国家,因此在整个岛屿上分配货物需要很高的成本。本文的目的是通过VRPTF方法、Hub-and-Spoke方法和Capacitated VRP方法进行成本比较,以便可能遇到类似情况的国家可以应用该方法,得到最优的路线模型。本研究是通过对一家生产不易变质产品的公司的案例研究进行的,该公司使用Excel中的Open Solver和VBA程序进行生成。研究表明,VRPTF方法比其他方法具有更优的成本。
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引用次数: 1
A Prediction of PM2.5 Concentration Based on Temporal-Spatial Fusion Model 基于时空融合模型的PM2.5浓度预测
Sifan Su, Cui Zhu, Wenjun Zhu, L. Kaunda
In this paper, a temporal-spatial fusion model is proposed for PM2.5 concentration prediction. The model uses historical PM2.5 concentration and meteorological data as input of the model to make hourly predictions of PM2.5 concentration. This model consists of three parts: 1) Long short-term memory neural network predictor based on time dimension, 2) Artificial neural network predictor based on spatial dimension, 3) Model tree predictor based on temporal-spatial fusion. This method combines the forecast results of two dimensions in space and time dynamically, as the spatial and temporal correlation of data is considered. Experimental results show this model performs better than predicting from a single dimension, confirming the effectiveness of the model.
本文提出了一种用于PM2.5浓度预测的时空融合模型。该模型使用历史PM2.5浓度和气象数据作为模型的输入,对每小时的PM2.5浓度进行预测。该模型由三个部分组成:1)基于时间维度的长短期记忆神经网络预测器,2)基于空间维度的人工神经网络预测器,3)基于时空融合的模型树预测器。该方法考虑了数据的时空相关性,将空间和时间两个维度的预测结果动态地结合起来。实验结果表明,该模型的预测效果优于单维度预测,验证了该模型的有效性。
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引用次数: 1
EMG Sensor System for Neck Fatigue Assessment Using RF Wireless Power Transmission 基于射频无线传输的颈部疲劳肌电传感器系统
Hyunwoo Choi
Though more and more people are feeling pain in the neck due to computer and smartphone usage, few equipment is available to measure neck fatigue. In this paper, we use radio frequency wireless power transmission (RF WPT) method to allow a small battery to be used while allowing continuous measurement for big data. Miniaturized electromyogram (EMG) sensor system with Arduino Pro mini can be lightly attached to the neck, giving the user notification of posture correction or stretching needs without additional neck fatigue. Information collected by EMG sensor system is sent to the users, which can prevent turtle neck syndrome and reduce the neck fatigue by long working hours.
虽然越来越多的人因为使用电脑和智能手机而感到颈部疼痛,但很少有设备可以测量颈部疲劳。在本文中,我们使用射频无线电力传输(RF WPT)方法,允许使用小电池,同时允许对大数据进行连续测量。使用Arduino Pro mini的小型化肌电图(EMG)传感器系统可以轻轻附着在颈部,在不增加颈部疲劳的情况下通知用户姿势纠正或拉伸需求。肌电传感器系统采集到的信息发送给使用者,可以预防龟颈综合征,减少长时间工作造成的颈部疲劳。
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引用次数: 6
NOx Prediction Method Based on Deep Extreme Learning Machine 基于深度极限学习机的NOx预测方法
Ying Li, Fanjun Li
Real-time prediction of NOx is important for the control of NOx emission from a coal-fired power plant. This paper presents a NOx prediction method based on deep extreme learning machine. First, an improved deep extreme learning machine is proposed. Then, a NOx prediction model is designed based on the proposed method. Finally, the model is evaluated by using the actual data. Simulations results show that the proposed method is effective.
NOx实时预测对于控制燃煤电厂NOx排放具有重要意义。提出了一种基于深度极限学习机的NOx预测方法。首先,提出了一种改进的深度极限学习机。在此基础上,设计了NOx预测模型。最后,用实际数据对模型进行了评价。仿真结果表明,该方法是有效的。
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引用次数: 0
Intuitionistic Fuzzy Inference System with Genetic Tuning for Predicting Financial Performance 基于遗传调谐的财务绩效预测直觉模糊推理系统
P. Hájek, V. Olej
Intuitionistic fuzzy inference systems are used to model the uncertainty associated with positive and negative information and preferences. Here, we propose a novel intuitionistic fuzzy inference system of the Takagi-Sugeno-Kang type with genetic tuning. A genetic fuzzy apriori algorithm is used to obtain both the set of if-then rules and the initial values of the premise parameters. Then, a genetic algorithm is applied to tune the premise and consequent parameters of the intuitionistic fuzzy inference system. We demonstrate the effectiveness of the proposed system for predicting corporate financial performance and show that the system has higher prediction accuracy than state-of-the-art fuzzy inference systems.
直觉模糊推理系统用于模拟与正、负信息和偏好相关的不确定性。在此,我们提出了一种新的带有遗传调谐的Takagi-Sugeno-Kang型直觉模糊推理系统。利用遗传模糊先验算法获得了假设-然后规则集和前提参数的初始值。然后,应用遗传算法对直觉模糊推理系统的前提参数和结果参数进行调整。我们证明了所提出的系统在预测公司财务绩效方面的有效性,并表明该系统比最先进的模糊推理系统具有更高的预测精度。
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引用次数: 1
Selection of Prefabricated Concrete Factories' Location Based on Triangular Fuzzy Numbers and Fuzzy Group Decision-Making 基于三角模糊数和模糊群决策的预制混凝土厂房选址
Lianbo Zhu, Xu Meng, Zhenqun Shi, Yilei Huang
In China, owing to some promotion policies of prefabricated buildings, the enterprises of precast concrete components grow by leaps and bounds. However, there are lots of influence factors of selecting PC factories' locations. It's a complex and multi-criteria decision-making problems. How to make a right decision is very important because the location will affect the operation cost and core competence. The paper puts forward four primary criterion: the geographical factors, economic factors, social and environmental factors on the basis of summarizing the related research results, combining with the experience of the experts and the characteristics of the precast concrete components techniques. There are total 19 secondary criteria under the primary ones. Then the paper presents a fuzzy group decision-making model based on the triangular fuzzy numbers. Finally an example is given to prove the model's validity and scientificity. The research result will provide a new method and idea to select the precast concrete factories' locations.
在中国,由于一些装配式建筑的推广政策,预制混凝土构件企业得到了突飞猛进的发展。然而,影响PC工厂选址的因素很多。这是一个复杂的多标准决策问题。如何做出正确的区位决策至关重要,因为区位会影响企业的经营成本和核心竞争力。本文在总结相关研究成果的基础上,结合专家的经验和混凝土预制构件技术的特点,提出了地理因素、经济因素、社会因素和环境因素四个主要评判标准。在主要标准之下共有19项次要标准。然后提出了一个基于三角模糊数的模糊群决策模型。最后通过算例验证了模型的有效性和科学性。研究结果将为混凝土预制厂房选址提供新的方法和思路。
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引用次数: 1
AUNTY: A Tool to Automatically Analyze Data Using Fuzzy Automata 使用模糊自动机自动分析数据的工具
Iván Calvo, Mercedes G. Merayo, Manuel Núñez
Recent work has shown that fuzzy bounds are an appropriate mechanism to decide the correctness of systems where some of the parameters governing their behavior have a degree of uncertainty. In order to provide a formalism to specify and analyze this type of systems, an extension of finiteautomata with fuzzy constraints has been introduced. Previous work has provided the theoretical framework and the application methodology. This framework has been used in different areas, in particular, in the analysis of electrocardiograms to detect abnormal patterns of behavior. Although our case studies were fully supported by a dedicated computer program, we missed a tool where the particular features of each system could be easily specified. In this paper we present AUNTY: a tool to AUtomatically aNalyze daTa using fuzzY automata. The tool allows users to graphically represent specifications of behaviors and automatically analyze whether the available data conforms to a specification. Its modular architecture makes the tool suitable to be adapted to a wide range of use cases.
最近的工作表明,模糊界限是一种适当的机制来决定系统的正确性,其中一些控制其行为的参数有一定程度的不确定性。为了提供一种描述和分析这类系统的形式化方法,引入了带模糊约束的有限自动机的扩展。先前的工作提供了理论框架和应用方法。这一框架已被用于不同的领域,特别是在分析心电图以检测异常行为模式方面。虽然我们的案例研究完全由专用的计算机程序支持,但我们错过了一个可以轻松指定每个系统的特定功能的工具。本文提出了一种利用模糊自动机自动分析数据的工具AUNTY。该工具允许用户以图形方式表示行为规范,并自动分析可用数据是否符合规范。它的模块化体系结构使该工具适合于适应广泛的用例。
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引用次数: 2
Regression Method for Noisy Inputs Based on Non-Parametric Estimator Constructed from Noiseless Training Data 基于无噪声训练数据构造的非参数估计的噪声输入回归方法
Ryo Hanafusa, T. Okadome
The regression method proposed in this paper determines a regression function for noisy inputs. We represent noisy inputs by using noise and latent noise-free constituent of the noisy input. Given an observed noisy input, the proposed method estimates the posterior of the latent noise-free constituent of it, and represents the posterior using the noise distribution. For the value of the regression function for the noisy input, the method produces the expected value of the Nadaraya–Watson estimator for noiseless inputs, which is constructed from a training dataset consisting of noiseless explanatory values and the corresponding objective values. In addition, a probabilistic generative model is presented for estimating the noise distribution. This enables us to determine the noise distribution parametrically from a single noisy input, using the distribution of the noise-free constituent of the noisy input estimated from the training dataset as a prior. Experiments conducted using artificial and real datasets show that the proposed method suppresses the overfitting of the regression function for noisy inputs and that the root mean squared errors of the predictions are smaller compared with those of an existing method.
本文提出的回归方法确定了噪声输入的回归函数。我们通过使用噪声和噪声输入的潜在无噪声成分来表示噪声输入。给定观察到的噪声输入,该方法估计其潜在无噪声成分的后验,并用噪声分布表示后验。对于有噪声输入的回归函数的值,该方法产生无噪声输入的Nadaraya-Watson估计器的期望值,该估计器由由无噪声解释值和相应的客观值组成的训练数据集构建。此外,提出了一种估计噪声分布的概率生成模型。这使我们能够从单个噪声输入参数化地确定噪声分布,使用从训练数据集中估计的噪声输入的无噪声成分的分布作为先验。利用人工数据集和真实数据集进行的实验表明,该方法抑制了回归函数对噪声输入的过拟合,并且预测的均方根误差比现有方法小。
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引用次数: 0
Combining Deep Learning and JSEG Cuda Segmentation Algorithm for Electrical Components Recognition 结合深度学习和JSEG Cuda分割算法的电子元件识别
F. Fambrini, D. G. Caetano, C. Moya, Guilherme Ferretti Grissi, Y. Iano
A segmentation and recognition system for thermographic images of electric power distribution network using Artificial Intelligence is proposed in this article. The infrared thermography is usually used to proceed inspections in electrical power distribution lines, assisted by a human operator, which is usually responsible for operating all the equipment, selecting the hottest spots in the image (corresponding to the places needing maintenance), making reports and calling the technical team, which will do the repairs. The proposed automatic diagnosis system aims to replace the manual inspection operation using image processing algorithms. A method of segmentation for thermal images known as JSEG is implemented and tested and a Convolution Neural Network is responsible to recognize the segmented elements. The results show the feasibility of the algorithm, and the monitoring system.
提出了一种基于人工智能的配电网热像图分割与识别系统。红外热像仪通常用于对配电线路进行检查,由操作员协助,操作员通常负责操作所有设备,选择图像中最热的点(对应需要维修的地方),制作报告并呼叫技术团队,技术团队将进行维修。该自动诊断系统旨在利用图像处理算法取代人工检测操作。实现并测试了一种称为JSEG的热图像分割方法,并使用卷积神经网络负责识别分割的元素。实验结果表明了该算法的可行性,以及该监控系统的可行性。
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引用次数: 1
Comparing Item Selection Criteria in Multidimensional Computerized Adaptive Testing for Two Item Response Theory Models 两种项目反应理论模型多维计算机自适应测试中项目选择标准的比较
Ziwen Ye, Jianan Sun
Multidimensional computerized adaptive testing is one of the most popular research issues in statistical and psychological measurement. The purpose of this study is to compare several commonly concerned item selection criteria in different typical testing conditions for dichotoumous and polytomous testing data. Two simulation studies were conducted to explore ability parameter estimation accuracy and item exposure rate for these criteria with the assumption of multidimensional two parameter logistic model and multidimensional graded response model could fit the testing data well, individually. Results showed that the criterion of Bayesian A-Optimality generally performs best both for the two item response theory models from the perspective of the above evaluation indices. As for the three-dimensional case based on the two models, A-Optimality was a relatively bad criterion in terms of ability parameter estimation accuracy.
多维计算机化自适应测试是统计和心理测量领域的研究热点之一。本研究的目的是比较在二分类和多分类测试数据的不同典型测试条件下几个常见的项目选择标准。在假设多维双参数logistic模型和多维分级反应模型能很好地拟合测试数据的情况下,分别对这些准则的能力参数估计精度和项目暴露率进行了模拟研究。结果表明,从上述评价指标来看,贝叶斯a -最优准则在两种项目反应理论模型中均表现最佳。对于基于这两种模型的三维情况,a - optimality在能力参数估计精度方面是一个相对较差的准则。
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引用次数: 3
期刊
2018 3rd International Conference on Computational Intelligence and Applications (ICCIA)
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