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Development of an intelligent Data-Driven System to Recommend Personalized Fashion Design Solutions

SENSORS 2021年第12期21卷 4239-4239页

作者： Sharma, Shukla Koehl, Ludovic Bruniaux, Pascal Zeng, Xianyi Wang, Zhujun Lab Genie & Mat Text GEMTEX F-59056 Roubaix France ENSAIT F-59056 Roubaix France Ecole Cent Lille F-59650 Lille France Donghua Univ Coll Fash & Design Shanghai 200051 Peoples R China Anhui Polytech Univ Sch Text & Garment Wuhu 241000 Peoples R China

In the context of fashion/textile innovations towards Industry 4.0, a variety of digital technologies, such as 3D garment CAD, have been proposed to automate, optimize design and manufacturing processes in the organizations of involved enterprises and supply chains as well as services such as marketing and sales. However, the current digital solutions rarely deal with key elements used in the fashion industry, including professional knowledge, as well as fashion and functional requirements of the customer and their relations with product technical parameters. Especially, product design plays an essential role in the whole fashion supply chain and should be paid more attention to in the process of digitalization and intelligentization of fashion companies. In this context, we originally developed an interactive fashion and garment design system by systematically integrating a number of data-driven services of garment design recommendation, 3D virtual garment fitting visualization, design knowledge base, and design parameters adjustment. This system enables close interactions between the designer, consumer, and manufacturer around the virtual product corresponding to each design solution. In this way, the complexity of the product design process can drastically be reduced by directly integrating the consumer's perception and professional designer's knowledge into the garment computer-aided design (CAD) environment. Furthermore, for a specific consumer profile, the related computations (design solution recommendation and design parameters adjustment) are performed by using a number of intelligent algorithms (BIRCH, adaptive Random Forest algorithms, and association mining) and matching with a formalized design knowledge base. The proposed interactive design system has been implemented and then exposed through the REST API, for designing garments meeting the consumer's personalized fashion requirements by repeatedly running the cycle of design recommendation-virtual gar

关键词： fashion design recommendation 3D virtual garment fitting design knowledge base intelligent algorithms

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Optimized trajectory planning for Cybernetic Transportation Systems

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IFAC-PapersOnLine 2016年第15期49卷 1-6页

作者： Garrido, Fernando González, David Milanés, Vicente Pérez, Joshué Nashashibi, Fawzi Team Inria 2 Rue Simonne Iff Paris75012 France Vedecom institute 77 Rue des Chantiers Versailles78000 France

This paper describes the development of an optimized path planning algorithm for automated vehicles in urban environments. This path planning is developed on the basis of urban environments, where Cybernetic Transportation Systems (CTS) will operate. Our approach is mainly affected by vehicle's kinematics and physical road constraints. Based on this assumptions, computational time for path planning can be significantly reduced by creating an off-line database that already optimized all the potential trajectories in each curve the CTS can carry out. Therefore, this algorithm generates a database of smooth and continuous curves considering a big set of different intersection scenarios, taking into account the constraints of the infrastructure and the physical limitations of the vehicle. According to the real scenario, the local planner selects from the database the appropriate curves from searching for the ones that fit with the intersections defined on it. The path planning algorithm has been tested in simulation using the previous control architecture. The results obtained show path generation improvements in terms of smoothness and continuity. Finally, the proposed algorithm was compared with previous path planning algorithms for its assessment. © 2016

关键词： Motion planning Cost functions Curve fitting Curves (road) Database systems Optimization Urban planning Urban transportation Vehicles Computational time Control architecture Cybernetic transportation systems intelligent algorithms Path planning algorithm Physical limitations Trajectory Planning Urban environments

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A new approach to mechanical brittleness index modeling based on conventional well logs using hybrid algorithms

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EARTH SCIENCE INFORMATICS 2023年第4期16卷 3387-3416页

作者： Talkhouncheh, Milad Zamanzadeh Davoodi, Shadfar Larki, Babak Mehrad, Mohammad Rashidi, Sina Vasfi, Maher Univ Garmsar Dept Petr Engn Garmsar Iran Tomsk Polytech Univ Sch Earth Sci & Engn Lenin Ave Tomsk Russia Islamic Azad Univ Dept Petr Engn Omidiyeh Branch Omidiyeh Iran Petr Univ Technol Put Dept Petr Engn Ahwaz Iran

Mechanical brittleness index (BImech) of the rock is a necessary parameter for selecting appropriate drilling bits and proper depth intervals for hydraulic fracturing. The BImech measurement is possible through continuous coring followed by laboratory tests, which are extremely cost- and time-intensive. Although petrophysical logs provide us with some continuous pieces of information, the complex nonlinear relationship between the logs and the BImech calls for implementing intelligent approaches before one can predict BImech from the petrophysical logs. Therefore, the present research is an attempt to develop BImech prediction models using least-squares support-vector machine (LSSVM) and multilayer perceptron (MLP) neural network (NN) as well as their hybrid forms with cuckoo optimization algorithm (COA), particle swarm optimization (PSO), and genetic algorithm (GA) on data from wells penetrating Maroon Oilfield. For this purpose, we began by approximating the BImech from the Poisson's ratio and static Young's modulus - with the later obtained from laboratory test results-calibrated petrophysical logs. Next, the entire set of available data was split into two subsets, namely modeling and validation subsets. Application of the second version of the nondominated sorting genetic algorithm (NSGA-II) combined with the MLP-NN for feature selection showed that, among the eight features considered, five made the best set for developing estimator models, including P- and S-wave velocities, depth, density (RHOB), and gamma-ray (GR) readings. Accordingly, intelligent algorithms were developed by means of these five features on the basis of the modeling data. Results of the training and testing phases showed that the hybrid algorithms were more accurate than the simple forms of either MLP or LSSVM. Among the hybrid algorithms, the highest levels of accuracy and generalizability were achieved with the LSSVM-COA. Application of the developed models on the validation data and a we

关键词： Mechanical brittleness index Feature selection intelligent algorithms Static Young's modulus Poisson's ratio

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Eight grand challenges for value sensitive design from the 2016 Lorentz workshop

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ETHICS AND INFORMATION TECHNOLOGY 2021年第1期23卷 5-16页

作者： Friedman, Batya Harbers, Maaike Hendry, David G. van den Hoven, Jeroen Jonker, Catholijn Logler, Nick Univ Washington Informat Sch Value Sensit Design Lab Seattle WA 98195 USA Rotterdam Univ Appl Sci Res Ctr Creating 010 Rotterdam Netherlands Delft Univ Technol Delft Design Values Inst Delft Netherlands Delft Univ Technol Fac EEMCS Interact Intelligence Grp Delft Netherlands Leiden Univ LIACS Leiden Netherlands

In this article, we report on eight grand challenges for value sensitive design, which were developed at a one-week workshop, Value Sensitive Design: Charting the Next Decade, Lorentz Center, Leiden, The Netherlands, November 14-18, 2016. A grand challenge is a substantial problem, opportunity, or question that motives sustained research and design activity. The eight grand challenges are: (1) Accounting for Power, (2) Evaluating Value Sensitive Design, (3) Framing and Prioritizing Values, (4) Professional and Industry Appropriation, (5) Tech policy, (6) Values and Human Emotions, (7) Value Sensitive Design and intelligent algorithms, and (8) Value Tensions. Each grand challenge consists of a discussion of its importance and a set of tractable key questions.

关键词： Value sensitive design Grand challenges Design research Power Evaluation Value prioritization Appropriation Tech policy Human emotions intelligent algorithms Value tensions

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Modelling and predicting energy consumption of a range extender fuel cell hybrid vehicle

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ENERGY 2018年第PartB期165卷 187-197页

作者： Zeng, Tao Zhang, Caizhi Hu, Minghui Chen, Yan Yuan, Changrong Chen, Jingrui Zhou, Anjian Chongqing Univ Sch Automot Engn Chongqing Automot Collaborat Innovat Ctr State Key Lab Mech Transmiss Chongqing 400044 Peoples R China Arizona State Univ Ira A Fulton Sch Engn Mesa AZ 85212 USA Arizona State Univ Polytech Sch Syst Engn Mesa AZ 85212 USA Changan Automobile Co Ltd Chongqing 400000 Peoples R China

Energy consumption is an important economical index of a fuel cell hybrid vehicle (FCHV). To analyse the energy consumption of a range extender FCHV and reduce the cost of experiments, this study developed a nonlinear regression model of the powertrain of the vehicle to predict the current and voltage on the DC bus, which were used in the investigation of energy consumption, by using the intelligent algorithms including Back Propagation neural network (BP), Genetic Algorithm-Back Propagation neural network (GABP) and least square support vector machine (LSSVM). The model based on the LSSVM achieves the best predicted performance and can consider the nonlinear characteristics of the powertrain quite well. A case study was discussed by applying the obtained model and integrated with a hierarchical energy management strategy (HEMS). The specific results of energy consumption showed that it is feasible to use the predicted data of the obtained model in the analysis of the energy consumption of the FCHV. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： Range extender Energy consumption intelligent algorithms Fuel cell hybrid vehicle

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Dissolved Gas Analysis Principle-Based intelligent Approaches to Fault Diagnosis and Decision Making for Large Oil-Immersed Power Transformers: A Survey

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ENERGIES 2018年第4期11卷 913页

作者： Cheng, Lefeng Yu, Tao South China Univ Technol Sch Elect Power Guangzhou 510640 Guangdong Peoples R China Guangdong Key Lab Clean Energy Technol Guangzhou 510640 Guangdong Peoples R China

Compared with conventional methods of fault diagnosis for power transformers, which have defects such as imperfect encoding and too absolute encoding boundaries, this paper systematically discusses various intelligent approaches applied in fault diagnosis and decision making for large oil-immersed power transformers based on dissolved gas analysis (DGA), including expert system (EPS), artificial neural network (ANN), fuzzy theory, rough sets theory (RST), grey system theory (GST), swarm intelligence (SI) algorithms, data mining technology, machine learning (ML), and other intelligent diagnosis tools, and summarizes existing problems and solutions. From this survey, it is found that a single intelligent approach for fault diagnosis can only reflect operation status of the transformer in one particular aspect, causing various degrees of shortcomings that cannot be resolved effectively. Combined with the current research status in this field, the problems that must be addressed in DGA-based transformer fault diagnosis are identified, and the prospects for future development trends and research directions are outlined. This contribution presents a detailed and systematic survey on various intelligent approaches to faults diagnosing and decisions making of the power transformer, in which their merits and demerits are thoroughly investigated, as well as their improvement schemes and future development trends are proposed. Moreover, this paper concludes that a variety of intelligent algorithms should be combined for mutual complementation to form a hybrid fault diagnosis network, such that avoiding these algorithms falling into a local optimum. Moreover, it is necessary to improve the detection instruments so as to acquire reasonable characteristic gas data samples. The research summary, empirical generalization and analysis of predicament in this paper provide some thoughts and suggestions for the research of complex power grid in the new environment, as well as reference

关键词： power transformer fault diagnosis and decision dissolved gas analysis intelligent algorithms reliability assessment hybrid network preventive electrical tests

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Data Asset Management and Visualization Based on intelligent Algorithm: Taking Power Equipment Data as An Example

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TEHNICKI VJESNIK-TECHNICAL GAZETTE 2022年第4期29卷 1109-1119页

作者： Xie, Xiaoming Peng, Yixuan YGsoft Inc Guangwai St Xicheng Dist 100044 Beiing Peoples R China

Data asset management is adequate in solving the problem of data silence and data idleness for enterprises. Through intelligent algorithms such as neural network, in-depth learning and block chain, and guided by business needs, it extracts, analyzes and visualizes the existing business precipitation data, and forms scattered and disordered data into valuable information to support the development of the company, so as to activate data assets. Taking the management data of electric power equipment as an example, this paper proposes a method of fusion of multiple intelligent control algorithms. The specific modules include the fusion of heterogeneous data;feature extraction of equipment asset management data based on machine learning;intelligent control of multi-objective optimization environment based on energy consumption data;BIM data visualization based on data classification-energy extraction-neural network (SVM-CART-SAE-DNN) algorithm fusion. The algorithm can effectively improve the efficiency of equipment management and enhance the security and economy of power infrastructure through intelligent control of equipment management.

关键词： data assets fusion intelligent algorithms management power equipment data visualization

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Effect of Size of Giant Component for actor node selection in WSANs: A comparison study

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CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE 2020年第8期32卷 e5106-e5106页

作者： Elmazi, Donald Cuka, Miralda Ikeda, Makoto Barolli, Leonard FIT Grad Sch Engn Fukuoka Japan FIT Dept Informat & Commun Engn Fukuoka Japan

Wireless Sensor and Actor Network (WSAN) is formed by the collaboration of micro-sensor and actor nodes. Whenever there is any special event, ie, fire, earthquake, flood or enemy attack in the network, sensor nodes have responsibility to sense it and send information towards an actor node. The actor node is responsible to take prompt decision and react accordingly. In this work, we propose and implement two Fuzzy Based Systems (FBS): FBS1 and FBS2 for actor selection in WSANs. Different from FBS1, in FBS2, we added the Size of Giant Component (SGC) as new parameter. The systems decide whether the actor will be selected for the required job or not, based on data supplied by sensors and actual actor condition. We evaluated the proposed system by computer simulations. Comparing FBS1 with FBS2, we can see that SGC parameter that is used in FBS2 gives to the system a better performance due to the growth of SGC parameter.

关键词： fuzzy logic Giant Component intelligent algorithms intelligent systems WSAN

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Research on mining land subsidence by intelligent hybrid model based on gradient boosting with categorical features support algorithm

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JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024年 354卷 120309页

作者： Zhang, Biao Xu, Chun Dai, Xingguo Xiong, Xin Cent South Univ Sch Resources & Safety Engn Changsha 410083 Hunan Peoples R China

Land subsidence induced by coal mining (MLS) has posed a huge threat to the ecological environment, buildings, roads, and other infrastructure safety in mining areas. However, the prediction and evaluation of MLS is relatively complex, and the reliability of the prediction results is closely related to factors such as the professional knowledge and engineering experience of researchers. This paper aims to combine intelligent optimization algorithms: ant lion optimizer (ALO), bald eagle search (BES), bird swarm algorithm (BSA), harris hawks optimization (HHO), and sparrow search algorithm (SSA), with machine learning model of gradient boosting with categorical features support algorithm (CatBoost) to predict MLS. To achieve this goal, five hybrid models based CatBoost were developed and the prediction accuracy and reliability of the models were compared and analyzed. The prediction performance of the hybrid models has been significantly improved on the basis of a single model, of which the SSA-CatBoost model has the most obvious improvement (from R2 = 0.927 to 0.965, RMSE = 0.541 to 0.377, MAE = 0.386 to 0.297, VAF = 92.720 to 95.837). The importance and predictive contribution of all input features to predictive labels were studied with the Shapley method. The research results indicate that hybrid model technology is a reliable MLS prediction method. This study can help mining technicians use machine learning methods to study the degree of MLS damage to the surface environment and provide scientific advanced prediction and evaluation for the protection and management of the ecological environment in mining areas and the formulation of safety production measures.

关键词： Coal mining Subsidence prediction intelligent algorithms Machine learning Shapley additive explanations

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ON THE PERFORMANCE OF STATIC AND DYNAMIC LOCATION MANAGEMENT STRATEGIES IN MOBILE COMPUTING

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INTERNATIONAL JOURNAL OF FOUNDATIONS OF COMPUTER SCIENCE 2011年第3期22卷 519-546页

作者： Taheri, Javid Zomaya, Albert Y. Univ Sydney Sch Informat Technol Ctr Distributed & High Performance Comp Sydney NSW 2006 Australia

This work reviews a number of algorithms to solve the location management problem in mobile networks for both static and dynamic scenarios. In the static mode, results of five algorithms are used to highlight the pros and cons for each algorithm. These results provide new insight into the mobility management problem that can influence the design of future wireless networks. In the dynamic mode in which mobile users' past movement patterns are used in making future paging decisions by the network, the performance of an online location management algorithm is examined under different deployment setups. Performance results of this algorithm show its advantages over the currently implemented and/or proposed static location management systems (including GSM).

关键词： Location management problem fuzzy logic intelligent algorithms

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