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| 1 | Pigeon-inspired optimization:a new swarm intelligence optimizer for air robot path planning显示文摘Purpose–The purpose of this paper is to present a novel swarm intelligence optimizer—pigeoninspired optimization(PIO)—and describe how this algorithm was applied to solve air robot path planning problems.Design/methodology/approach–The formulation of threat resources and objective function in air robot path planning is given.The mathematical model and detailed implementation process of PIO is presented.Comparative experiments with standard differential evolution(DE)algorithm are also conducted.Findings–The feasibility,effectiveness and robustness of the proposed PIO algorithm are shown by a series of comparative experiments with standard DE algorithm.The computational results also show that the proposed PIO algorithm can effectively improve the convergence speed,and the superiority of global search is also verified in various cases.Originality/value–In this paper,the authors first presented a PIO algorithm.In this newly presented algorithm,map and compass operator model is presented based on magnetic field and sun,while landmark operator model is designed based on landmarks.The authors also applied this newly proposed PIO algorithm for solving air robot path planning problems. | Haibin Duan Peixin Qiao | 2014 | International Journal of Intelligent Computing and Cybernetics2014，7，1： | 17 |
| 2 | Discrete-time based sliding-mode control of robot manipulators显示文摘Purpose-The purpose of this paper is to develop sliding mode control with linear and nonlinear manifolds in discrete-time domain for robot manipulators.Design/methodology/approach–First,a discrete linear sliding mode controller is designed to an n-link robot based on Gao’s reaching law.In the second step,a discrete terminal sliding mode controller is developed to design a finite time and high precision controller.The stability analysis of both controllers is presented in the presence of model uncertainties and external disturbances.Finally,sampling time effects on the continuous-time system outputs and sliding surfaces are discussed.Findings–Computer simulations on a three-link SCARA robot show that the proposed controllers are robust against model uncertainties and external disturbance.It was also shown that the sampling time has important effects on the closed loop system stability and convergence.Practical implications-The proposed controllers are low cost and easily implemented in practice in comparison with continuous-time ones.Originality/value-The novelty associated with this paper is the development of an approach to finite time and robust control of n-link robot manipulators in discrete-time domain.Also,obtaining an upper bound for the sampling time is another contribution of this work. | Sajjad Shoja Majidabad Heydar Toosian Shandiz | 2012 | International Journal of Intelligent Computing and Cybernetics2012，5，3： | 2 |
| 3 | Chattering-free sliding mode control with unidirectional auxiliary surfaces for miniature helicopters显示文摘Purpose-This article proposes a chattering-free sliding mode control scheme with unidirectional auxiliary surfaces(UAS-SMC)for small miniature autonomous helicopters(Trex 250).Design/methodology/approach-The proposed UAS-SMC scheme consists of a nested sequence of rotor dynamics,angular rate,Euler angle,velocity and position loops.Findings-It is demonstrated that the UAS-SMC strategy can eliminate the chattering phenomenon exhibiting in the convenient SMC method and achieve a better approaching speed.Originality/value-The proposed control strategy is implemented on the helicopter and flight tests clearly demonstrate that a much better performance could be achieved,compared with convenient SMC schemes. | Jian Fu Wen-hua Chen Qing-xian Wu | 2012 | International Journal of Intelligent Computing and Cybernetics2012，5，3： | 2 |
| 4 | Receding horizon control for cooperative search of multi-UAVs based on differential evolution显示文摘Purpose–The purpose of this paper is to present a hybrid method of intelligent optimization algorithm and Receding Horizon Control.The method is applied to solve the problem of cooperative search of multi-unmanned aerial vehicles(multi-UAVs).Design/methodology/approach–The intelligent optimization of Differential Evolution(DE)makes the complex problem of multi-UAVs cooperative search a regular function optimization problem.To meet the real-time requirement,the idea of Receding Horizon Control is applied.An Extended Search Map based on hormone information is used to describe the uncertain environment information.Findings–Simulation results indicate effectiveness of the hybrid method in solving the problem of cooperative search for multi-UAVs.Originality/value–The paper presents an interesting hybrid method of DE and Receding Horizon Control for the problem of cooperative multi-UAVs. | Zhenyu Zhao Guangshan Lu | 2012 | International Journal of Intelligent Computing and Cybernetics2012，5，1： | 2 |
| 5 | Real-Time Safety Helmet Detection Using Yolov5 at Construction Sites显示文摘The construction industry has always remained the economic and social backbone of any country in the world where occupational health and safety(OHS)is of prime importance.Like in other developing countries,this industry pays very little,rather negligible attention to OHS practices in Pakistan,resulting in the occurrence of a wide variety of accidents,mishaps,and near-misses every year.One of the major causes of such mishaps is the non-wearing of safety helmets(hard hats)at construction sites where falling objects from a height are unavoid-able.In most cases,this leads to serious brain injuries in people present at the site in general and the workers in particular.It is one of the leading causes of human fatalities at construction sites.In the United States,the Occupational Safety and Health Administration(OSHA)requires construction companies through safety laws to ensure the use of well-defined personal protective equipment(PPE).It has long been a problem to ensure the use of PPE because round-the-clock human monitoring is not possible.However,such monitoring through technological aids or automated tools is very much possible.The present study describes a systema-tic strategy based on deep learning(DL)models built on the You-Only-Look-Once(YOLOV5)architecture that could be used for monitoring workers’hard hats in real-time.It can indicate whether a worker is wearing a hat or not.The proposed system usesfive different models of the YOLOV5,namely YOLOV5n,YOLOv5s,YOLOv5 m,YOLOv5l,and YOLOv5x for object detection with the support of PyTorch,involving 7063 images.The results of the study show that among the DL models,the YOLOV5x has a high performance of 95.8%in terms of the mAP,while the YOLOV5n has the fastest detection speed of 70.4 frames per second(FPS).The proposed model can be successfully used in practice to recognize the hard hat worn by a worker. | Kisaezehra Muhammad Umer Farooq Muhammad Aslam Bhutto Abdul Karim Kazi | 2023 | Intelligent Automation & Soft Computing2023，，4： | 2 |
| 6 | Transferring case knowledge to adaptation knowledge: an approach for case-base maintenance显示文摘 | Shiu S C K | 2001 | Computational Intelligence2001，17，2： | 2 |
| 7 | The usefulness of machine learning approach to knowledge acquisition显示文摘 | Grzymala Bausse D M Grzymala Busse J W | 1995 | Computational Intelligence1995，11，2： | 2 |
| 8 | Learning in relational databases: a rough set approach 显示文摘 | Hu X H Cercone N | 1995 | International Journal of Computational Intelligence1995，11，2： | 2 |
| 9 | Rough set reduction of attributes and their domains for neural networks 显示文摘 | Jelonek J Krawiec K Slowinski R | 1995 | Computational Intelligence1995，11，2： | 2 |
| 10 | Deep Learning Prediction Model for Heart Disease for Elderly Patients显示文摘The detection of heart disease is a problematic task in medical research.This diagnosis utilizes a thorough analysis of the clinical tests from the patient’s medical history.The massive advances in deep learning models pursue the devel-opment of intelligent computerized systems that aid medical professionals to detect the disease type with the internet of things support.Therefore,in this paper,we propose a deep learning model for elderly patients to aid and enhance the diag-nosis of heart disease.The proposed model utilizes a deeper neural architecture with multiple perceptron layers with regularization learning techniques.The mod-el performance is verified with a full and minimum set of features.Fewer features enhance the processing time of the classification process while the accuracy is compromised.The performance of classifiers with less features has been analyzed with experimental results.The proposed system is built on the Internet of Things Platform for medical data for the classification process which aids medical profes-sionals to detect heart diseases through cloud platforms.The results accuracy is matched to classical learning models such as Convolutional Neural Network(CNN),Deep CNN,and neural ensemble models.The analysis of the proposed diagnostic system can determine the heart disease risks efficiently.Experimental results demonstrate thatflexible modeling and tuning of the hyperparameters can attain an accuracy of up to 97.11%. | Abeer Abdulaziz AlArfaj Hanan Ahmed Hosni Mahmoud | 2023 | Intelligent Automation & Soft Computing2023，，2： | 2 |
| 11 | Hyperparameter Tuning for Deep Neural Networks Based Optimization Algorithm显示文摘For training the present Neural Network(NN)models,the standard technique is to utilize decaying Learning Rates(LR).While the majority of these techniques commence with a large LR,they will decay multiple times over time.Decaying has been proved to enhance generalization as well as optimization.Other parameters,such as the network’s size,the number of hidden layers,drop-outs to avoid overfitting,batch size,and so on,are solely based on heuristics.This work has proposed Adaptive Teaching Learning Based(ATLB)Heuristic to identify the optimal hyperparameters for diverse networks.Here we consider three architec-tures Recurrent Neural Networks(RNN),Long Short Term Memory(LSTM),Bidirectional Long Short Term Memory(BiLSTM)of Deep Neural Networks for classification.The evaluation of the proposed ATLB is done through the various learning rate schedulers Cyclical Learning Rate(CLR),Hyperbolic Tangent Decay(HTD),and Toggle between Hyperbolic Tangent Decay and Triangular mode with Restarts(T-HTR)techniques.Experimental results have shown the performance improvement on the 20Newsgroup,Reuters Newswire and IMDB dataset. | D.Vidyabharathi V.Mohanraj | 2023 | Intelligent Automation & Soft Computing2023，，6： | 2 |
| 12 | Identifying Global Exceptional Patterns in Muhi-database Mining显示文摘 | Zhang Chengqi Liu Meiling Nie Wen long Zhang Shichao | 2004 | IEEE Computational Intelligence Bulletin2004，3，1： | 1 |
| 13 | On Knowledge Grid and Grid Intelligence显示文摘 | William K | 2005 | Computational Intelligence2005，21，2： | 1 |
| 14 | Learning in relational database: a rough set approach显示文摘 | Hu X Cerccone N | 1995 | Computational Intelligence1995，2，： | 1 |
| 15 | Learning in relational datbases:a rough set approach显示文摘 | Cercone N | 1995 | Computational Intelligence1995，11，2： | 1 |
| 16 | Incremental concept formation algorithms based on calois (concept) lattices显示文摘 | Godin R Missaoui R Alaoui H | 1995 | Computational Intelligence1995，11，2： | 1 |
| 17 | Learning in relational databases: a rough set approach显示文摘 | HU X H NICK C | 1995 | International Journal of Computational Intelligence1995，11，2： | 1 |
| 18 | Recent advances in cluster analysis显示文摘 | RUI X DONALD C WUNSCH I | 2008 | International Journal of Intelligent Computing and Cybernetics2008，1，4： | 1 |
| 19 | Multiword Expres- sions: A Pain in the Neck for NLP显示文摘 | SAG I BALDWIN T BOND F | 2002 | Computational Lin- guistics and Intelligent Text Processing2002，，： | 1 |
| 20 | Cooperative Robotics for Multi-Target Observation 显示文摘 | LynneEParker | 1999 | Intelligent Automation and Soft Computing special issue on Robotics Research at OakRidge National Laboratory1999，5，1： | 1 |
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