共查询到20条相似文献，搜索用时 31 毫秒
1.
Anwer Mustafa Hilal Badria Sulaiman Alfurhood Fahd N. Al-Wesabi Manar Ahmed Hamza Mesfer Al Duhayyim Huda G. Iskandar 《计算机、材料和连续体（英文）》2022,71(1):143-157
Smart city promotes the unification of conventional urban infrastructure and information technology (IT) to improve the quality of living and sustainable urban services in the city. To accomplish this, smart cities necessitate collaboration among the public as well as private sectors to install IT platforms to collect and examine massive quantities of data. At the same time, it is essential to design effective artificial intelligence (AI) based tools to handle healthcare crisis situations in smart cities. To offer proficient services to people during healthcare crisis time, the authorities need to look closer towards them. Sentiment analysis (SA) in social networking can provide valuable information regarding public opinion towards government actions. With this motivation, this paper presents a new AI based SA tool for healthcare crisis management (AISA-HCM) in smart cities. The AISA-HCM technique aims to determine the emotions of the people during the healthcare crisis time, such as COVID-19. The proposed AISA-HCM technique involves distinct operations such as pre-processing, feature extraction, and classification. Besides, brain storm optimization (BSO) with deep belief network (DBN), called BSO-DBN model is employed for feature extraction. Moreover, beetle antenna search with extreme learning machine (BAS-ELM) method was utilized for classifying the sentiments as to various classes. The use of BSO and BAS algorithms helps to effectively modify the parameters involved in the DBN and ELM models respectively. The performance validation of the AISA-HCM technique takes place using Twitter data and the outcomes are examined with respect to various measures. The experimental outcomes highlighted the enhanced performance of the AISA-HCM technique over the recent state of art SA approaches with the maximum precision of 0.89, recall of 0.88, F-measure of 0.89, and accuracy of 0.94. 相似文献
2.
空间飞行器故障诊断技术的发展和展望 总被引：3，自引：0，他引：3
由于空间飞行器需要高指标的安全保障，故障诊断成为极紧迫的任务，本文将评述空间飞行器故障诊断的重要性和特点，讨论空间飞行器故障诊断系统的结构和故障诊断技术，展望空间飞行器智能故障诊断技术的前景。 相似文献
3.
4.
Manar Ahmed Hamza Noha Negm Shaha Al-Otaibi Amel A. Alhussan Mesfer Al Duhayyim Fuad Ali Mohammed Al-Yarimi Mohammed Rizwanullah Ishfaq Yaseen 《计算机、材料和连续体（英文）》2022,72(3):4541-4557
Machine learning (ML) becomes a familiar topic among decision makers in several domains, particularly healthcare. Effective design of ML models assists to detect and classify the occurrence of diseases using healthcare data. Besides, the parameter tuning of the ML models is also essential to accomplish effective classification results. This article develops a novel red colobuses monkey optimization with kernel extreme learning machine (RCMO-KELM) technique for epileptic seizure detection and classification. The proposed RCMO-KELM technique initially extracts the chaotic, time, and frequency domain features in the actual EEG signals. In addition, the min-max normalization approach is employed for the pre-processing of the EEG signals. Moreover, KELM model is used for the detection and classification of epileptic seizures utilizing EEG signal. Furthermore, the RCMO technique was utilized for the optimal parameter tuning of the KELM technique in such a way that the overall detection outcomes can be considerably enhanced. The experimental result analysis of the RCMO-KELM technique has been examined using benchmark dataset and the results are inspected under several aspects. The comparative result analysis reported the better outcomes of the RCMO-KELM technique over the recent approaches with the of 0.956. 相似文献
5.
目的为了能更有效、准确地对复杂设备进行状态监测和故障诊断。方法综述近年故障诊断技术中重要方法的基本原理、特点、局限性和研究现状。在大量文献的基础上,基于计算机技术、信号处理技术、人工智能技术和互联网技术讨论现代故障诊断技术的发展趋势。结果故障诊断技术主要研究机器或机组运行状态的变化在诊断信息中的反映,分为基于模型、基于信号和基于人工智能等3类。结论随着基础学科和前沿学科的不断发展和交叉渗透,故障诊断技术也在不断创新,未来的发展趋势主要集中于将不同人工智能技术以某种方式结合、集成或融合以及开放式远程协作诊断技术。 相似文献
6.
人工神经网络和机械故障诊断 总被引：33，自引：1，他引：33
智能化诊断是现代故障诊断技术发展的主要趋势,人工神经网络技术的出现为这种智能化提供了一个全新的途径。本文首先简单介绍了人工神经网络的基本性能及几个重要模型,着重探讨了人工神经网络技术在机械故障诊断领域中预测与控制、工况监测与故障分类诊断、模糊诊断和基于专家系统的故障诊断等几个主要方面的应用,指出人工神经网络技术与现有的信号处理、模式识别、模糊逻辑、专家系统等技术相结合,以解决故障信号分析与处理、故障模式识别以及故障论域专家知识的组织和推理等问题,必将加快智能化诊断发展的进程。可以预料:基于人工神经网络的故障诊断技术将具有广阔的发展与应用前景,并且随着VLsI 技术的发展,这一新技术必将广泛地应用于各种诊断实例。最后讨论了进一步值得研究的方向。 相似文献
7.
8.
Souad Larabi-Marie-Sainte Eatedal Alabdulkreem Mohammad Alamgeer Mohamed K Nour Anwer Mustafa Hilal Mesfer Al Duhayyim Abdelwahed Motwakel Ishfaq Yaseen 《计算机、材料和连续体（英文）》2022,72(3):4589-4601
Electroencephalography (EEG) eye state classification becomes an essential tool to identify the cognitive state of humans. It can be used in several fields such as motor imagery recognition, drug effect detection, emotion categorization, seizure detection, etc. With the latest advances in deep learning (DL) models, it is possible to design an accurate and prompt EEG EyeState classification problem. In this view, this study presents a novel compact bat algorithm with deep learning model for biomedical EEG EyeState classification (CBADL-BEESC) model. The major intention of the CBADL-BEESC technique aims to categorize the presence of EEG EyeState. The CBADL-BEESC model performs feature extraction using the ALexNet model which helps to produce useful feature vectors. In addition, extreme learning machine autoencoder (ELM-AE) model is applied to classify the EEG signals and the parameter tuning of the ELM-AE model is performed using CBA. The experimental result analysis of the CBADL-BEESC model is carried out on benchmark results and the comparative outcome reported the supremacy of the CBADL-BEESC model over the recent methods. 相似文献
9.
基于局域波信息熵的高速自动机故障诊断 总被引：1，自引：0，他引：1
针对小口径火炮自动机工作时产生的短时冲击信号,提出一种将局域波分解与信息熵相结合提取特征量,并利用Elman神经网络进行故障识别的诊断方法。首先运用具有自适应特性的局域波对振动信号进行分解得到IMF分量,再接着利用信息熵理论提取IMF信息熵、局域波能谱熵及能矩谱熵作为故障特征量,最后将特征向量输入Elman神经网络进行故障分类识别。实验结果表明:该方法能准确,有效地识别故障。 相似文献
10.
人工智能对交互设计的影响研究 总被引：9，自引：9，他引：0
目的人工智能对交互的感知方式及认知逻辑影响较大,交互设计的方法、交互设计的流程、认知心智模型、交互技术及交互界面的表现方式在人工智能的影响下,已经发生颠覆式改变。交互设计面对新的技术变化,需要从技术哲学与创新思维及设计技法方面进行新的探索。方法通过文献综述人工智能的发展历史,对比研究人类智能与人工智能的差异关系,结合无人驾驶车产品服务系统的交互设计等案例分析,提出混合智能的概念,辨析人工智能与人类智慧混合作用于交互设计所带来的变化。结论混合智能对交互设计方法流程、设计细则、设计评判都会有新的特征表现,通过人工智能产品交互设计,印证人工智能对交互设计带来的深刻影响。 相似文献
11.
12.
Edyta Hetmaniok 《Inverse Problems in Science & Engineering》2016,24(5):889-900
The paper presents a solution of the inverse problem consisting in reconstruction of the heat flux and the distribution of temperature in the process of binary alloy solidification when the temperature measurements in the selected points of the alloy are known. The considered task is mathematically modelled by means of the heat conduction equation with the substitute thermal capacity and with the liquidus and solidus temperatures varying in dependence on the concentration of the alloy component, whereas for describing the concentration the lever arm model is applied. An important part of the procedure consists in minimization of some functional executed with the aid of ACO algorithm. 相似文献
13.
目的 随着人工智能技术和设计软件的广泛应用,研究设计师在知识结构和专业能力方面的新需求,并建构人工智能背景下设计师胜任力模型。方法 以文献研究为基础,筛选人工智能背景下设计师胜任力因子,通过专家调研和访谈法获取专家信度,再通过设计师问卷调查和数据分析验证胜任力模型的有效性。结果 设计师除了应具有基本的设计专业技能和设计专业知识以外,还需要具有跨专业整合协调能力,具有跨学科和终生成长的知识结构、人工智能及大数据背景的基础知识,能运用人工智能软件辅助设计信息整理及提高设计流程的能力。同时,更高层次需要设计师能掌握人工智能编程语言,设计数据模型和算法指导机器如何做设计的能力。研究最终分析得出包含4个一级胜任力因子和17个二级胜任力因子的设计师胜任力模型。结论 该胜任力模型的建立明确了设计师在知识、专业能力、创新能力和人工智能技术应用能力方面的新需求,实现了人机能力优缺互补,达到更高效的设计能力水平,同时为高等院校设计人才培养以及设计职业资格评定制度提供了重要的理论支撑。 相似文献
14.
目的 从设计学视角探讨如何利用人工智能技术辅助创意激发。方法 以提高创意激发水平为导向,共召集18名设计专业学生分次使用传统搜索和文生图AI来进行用户体验测试,通过量表、访谈及非参与式观察收集定量定性数据进行模式分析,验证人工智能辅助创意激发的有效性。结果 人工智能辅助可以有效降低脑力负荷,减轻工作负担,支持设计师在创意探索和表达方面的活动。然而,与参与者主观感受相悖,人工智能实际未能显著提高参与者设计输出的新颖性和质量。对人工智能辅助下设计师行为特征进行分析,提炼出人工智能生成内容(AIGC)辅助创意激发的2种模式,代理型用户“委托-采纳”行为模式,表现为“委托主体-接纳偏差-采纳结果”;协同型用户“辅助-迭代”行为模式,表现为“独立拆解-排斥偏差-反复迭代”。结论 用户实验验证了人工智能在辅助创意激发上的能力,归纳了2类设计师的行为模式及成因,为后续人工智能赋能传统设计流程提供了新的研究思路。 相似文献
15.
ZHOU Yong PENG Fang-yu CHEN Ji-hong LI Bin 《国际设备工程与管理》2007,12(3):171-180
Based on the evaluation of dynamic performance for feed drives in machine tools, this paper presents a two-stage tuning method of servo parameters. In the first stage, the evaluation of dynamic performance, parameter tuning and optimization on a mechatronic integrated system simulation platform of feed drives are performed. As a result, a servo parameter combination is acquired. In the second stage, the servo parameter combination from the first stage is set and tuned further in a real machine tool whose dynamic performance is measured and evaluated using the cross grid encoder developed by Heidenhain GmbH. A case study shows that this method simplifies the test process effectively and results in a good dynamic performance in a real machine tool. 相似文献
16.
Subrata Dasgupta 《Sadhana》1994,19(1):5-21
A substantial part of the intellectual content of what H A Simon called the ‘sciences of the artificial’ is contained in the
activity we calldesign. A central aim ofdesign theory is to construct testable, explanatory models of the design process that will serve to enhance our understanding of how artifacts
are, or can be, designed. In this paper, we discuss how some of the basic concepts underlying the discipline ofartificial intelligence (ai) can serve to provide anexplanatory paradigm for understanding design. We present an AI-based model of the design process and describe some of the implications of this
model for our understanding of design — including that aspect of it we call ‘invention’. 相似文献
17.
Jothiraj Selvaraj;A. K. Jayanthy; 《International journal of imaging systems and technology》2024,34(2):e23034
The colorectal cancer (CRC) is gaining attention in the context of gastrointestinal tract diseases as it ranks third among the most prevalent type of cancer. The early diagnosis of the CRC can be done by periodic examination of the colon and rectum for innocuous tissue abnormality called polyp as it has the potential to evolve as malignant in future. The CRC diagnosis using wireless capsule endoscopy requires the dedicated commitment of the medical expert demanding significant time, focus and effort. The accuracy of manual analysis in identifying polyps is extensively reliant on the cognitive condition of the physician, thus emphasizing the requirement for automatic polyp identification. The artificial intelligence integrated computer-aided diagnosis system could assist the clinician in better diagnosis, thereby reducing the miss-rates of polyps. In our proposed study, we developed an application program interface to aid the clinician in automatic segmentation of the polyp and evaluation of its dimension by manual placement of four landmarks on the predicted polyp. The segmentation is performed by the proposed light weight Padded U-Net for the effective polyp segmentation in the colorectal images. We trained and validated the Padded U-Net with augmented images of Kvasir dataset and calculated the performance parameters. In order to facilitate image augmentation, a graphical user interface called Augment Tree was developed, which incorporates 92 augmentation techniques. The accuracy, recall, precision, IoU, F1-score, loss achieved during validation of Padded U-Net were 95.6%, 0.946%, 0.985%, 0.933%, 0.965% and 0.080% respectively. We demonstrated that accuracy was improved and loss was reduced when the model was trained with augmented images rather than only the limited original dataset images. On comparison of our Padded U-net architecture with recently developed architectures, our model attained optimal performance in all the metrics except accuracy in which it attained marginal performance to the highest value. 相似文献
18.
Statistical process control (SPC) is one of the most effective tools of total quality management, the main function of which is to monitor and minimize process variations. Typically, SPC applications involve three major tasks in sequence: (1) monitoring the process, (2) diagnosing the deviated process and (3) taking corrective action. With the movement towards a computer integrated manufacturing environment, computer based applications need to be developed to implement the various SPC tasks automatically. However, the pertinent literature shows that nearly all the researches in this field have only focussed on the automation of monitoring the process. The remaining two tasks still need to be carried out by quality practitioners. This project aims to apply a hybrid artificial intelligence technique in building a real time SPC system, in which an artificial neural network based control chart monitoring sub‐system and an expert system based control chart alarm interpretation sub‐system are integrated for automatically implementing the SPC tasks comprehensively. This system was designed to provide the quality practitioner with three kinds of information related to the current status of the process: (1) status of the process (in‐control or out‐of‐control). If out‐of‐control, an alarm will be signaled, (2) plausible causes for the out‐of‐control situation and (3) effective actions against the out‐of‐control situation. An example is provided to demonstrate that hybrid intelligence can be usefully applied for solving the problems in a real time SPC system. Copyright © 2003 John Wiley & Sons, Ltd. 相似文献
19.
Abstract The dynamic model of a manipulator system is a time‐varying highly nonlinear coupling equation set. When the moving speed increases or the payload, compared to its own weight, is no longer small, the performance of the conventional control schemes is not satisfactory for precision industrial application. Here a new adaptive control approach is developed for the manipulators to solve these problems. This algorithm directly uses a nonlinear dynamic model in the controller design to account for the nonlinear effects of the system. The least‐square time‐varying parameter identification scheme has been used to identify the change in configuration and payload. The simulation results show that this new approach has a very good trajectory tracking performance. 相似文献
20.
Machine intelligence is increasingly entering roles that were until recently dominated by human intelligence. As humans now depend upon machines to perform various tasks and operations, there appears to be a risk that humans are losing the necessary skills associated with producing competitively advantageous decisions. Therefore, this research explores the emerging area of human versus machine decision-making. An illustrative engineering case involving a joint machine and human decision-making system is presented to demonstrate how the outcome was not satisfactorily managed for all the parties involved. This is accompanied by a novel framework and research agenda to highlight areas of concern for engineering managers. We offer that the speed at which new human-machine interactions are being encountered by engineering managers suggests that an urgent need exists to develop a robust body of knowledge to provide sound guidance to situations where human and machine decisions conflict. Human-machine systems are becoming pervasive yet this research has revealed that current technological approaches are not adequate. The engineering insights and multi-criteria decision-making tool from this research significantly advance our understanding of this important area. 相似文献
