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MYOCARDIAL INFARCTION DETECTION USING intelligent algorithms

NEURAL NETWORK WORLD 2016年第1期26卷 91-110页

作者： Seenivasagam, V. Chitra, R. Natl Engn Coll Dept Comp Sci & Engn Kovilpatti India Noorul Islam Ctr Higher Educ Dept Comp Sci & Engn Kanyakumari Tamil Nadu India

Myocardial Infarction (MI) also known as heart attack is one of the most dangerous cardiovascular diseases. Accurate early prediction can effectively reduce the mortality rate caused by MI. The early stages of MI may only have subtle indications which can be varied in variable risk factors and making diagnosis difficult even for experienced cardiologists. In this paper the computer aided detection system is proposed to find the risk level of MI using the supervised classifier. The MI prediction system is developed using Feed Forward Neural Network (FFNN), Cascade Correlation Neural Network (CNN), and Support Vector Machine (SVM). Genetic Optimized Neural Network (GAANN), Particle Swarm Optimized Neural Network (PSONN) and also the performance of the Computer Aided Detection system is analyzed using various performance metrics.

关键词： intelligent algorithms risk factors myocardial infarction feed forward neural network computer aided detection

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Topologies and performance of intelligent algorithms: a comprehensive review

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ARTIFICIAL INTELLIGENCE REVIEW 2018年第1期49卷 79-103页

作者： Nabaei, Armin Hamian, Melika Parsaei, Mohammad Reza Safdari, Reza Samad-Soltani, Taha Zarrabi, Houman Ghassemi, A. Azad Univ Dept Comp Engn Tehran Iran PNU Dept Engn Tehran Iran Shiraz Univ Technol Dept Comp Engn & Informat Technol Shiraz Iran Univ Tehran Med Sci Sch Allied Med Sci Dept Hlth Informat Technol Tehran Iran ICT Res Inst Tehran Iran

Recently, optimization makes an important role in our day-to-day life. Evolutionary and population-based optimization algorithms are widely employed in several of engineering areas. The design of an optimization algorithm is a challenging endeavor caused of physical phenomena in order to obtain appropriate local and global search operators. Generally, local operators are fast. In contrast, global operators are used to find best solution in the search space;therefore they are slower compare to the local ones. The best review-knowledge of papers show that there are many optimization algorithms such as genetic algorithm, particle swarm optimization, artificial bee colony and etc in the engineering as a powerful tools. However, there is not a comprehensive review for theirs topologies and performance;therefore, the main goal of this paper is filling of this scientific gap. Moreover, several aspects of optimization heuristic designs and analysis are discussed in this paper. As a result, detailed explanation, comparison, and discussion on AI are achieved. Furthermore, some future research fields on AI are well summarized.

关键词： Optimization intelligent algorithms Review

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Concept, Principle and Application of Dynamic Configuration for intelligent algorithms

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IEEE SYSTEMS JOURNAL 2014年第1期8卷 28-42页

作者： Tao, Fei Laili, Yuanjun Liu, Yilong Feng, Ying Wang, Qining Zhang, Lin Xu, Lida Beihang Univ Sch Automat Sci & Elect Engn Beijing 100191 Peoples R China Peking Univ Coll Engn Intelligent Control Lab Beijing 100871 Peoples R China Old Dominion Univ Dept Informat Technol & Decis Sci Norfolk VA 23529 USA

Since genetic algorithm (GA) presented decades ago, large amount of intelligent algorithms and their improvements and mixtures have been putting forward one after another. However, little works have been done to extend their applications and verify their competence in different problems. For each specific complex problem, people always take a long time to find appropriate intelligent algorithm and develop improvements. To overcome these shortcomings, new dynamic configuration methods for intelligent algorithms (DC-IA) is presented in this paper on the basis of the requirements of three kinds of algorithm users. It separates the optimization problems and intelligent algorithms, modularizes each step of algorithms and extracts their core operators. Based on the coarse-grained operator modules, three-layer dynamical configurations, i.e., parameter-based configuration, operator-based configuration and algorithm-based configuration, are fully exploited and implemented. Under these methods, dozens of hybrid and improved intelligent algorithms can be easily produced in a few minutes just based on several configurable operator modules. Also, problem-oriented customizations in configurations can further extend the application range and advance the efficiency of the existing operators enormously. Experiments based on the established configuration platform verify the new configuration ways of applying and improving intelligent algorithm for both numerical and combinatorial optimization problems in industries on aspects of flexibility, robustness, and reusability.

关键词： Algorithm-based configuration dynamic configuration intelligent algorithms operator-based configuration optimization parameter-based configuration

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Research on Mobile Edge Computing Task Unloading Model Optimization and intelligent algorithms

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INTERNATIONAL JOURNAL OF UNCERTAINTY FUZZINESS AND KNOWLEDGE-BASED SYSTEMS 2024年第7期32卷 1051-1073页

作者： Wu, Beijia Zhejiang Univ Sch Publ Adm Hangzhou 310000 Zhejiang Peoples R China

To overcome the limitations of mobile devices in executing computing-intensive workloads, mobile edge computing emerged at the times required. It can effectively support computing intensive and delay critical applications executed by Internet of Things devices with limited computing power and energy constraints and becomes the key technology of next-generation networks. This research first determined the optimization framework of the mobile edge computing task unloading system, built a basic platform for mobile edge computing task unloading after system optimization, completed the drill transformation of intelligent algorithm based on the mobile edge computing task unloading algorithm of the optimized system, and studied its convergence and applicability. Finally, by comparing several different mobile edge computing tasks unloading models, Select a suitable mobile edge computing task unloading model, and complete the practical effect test. The results show that: (1) Compared with the traditional unloading mode, the optimized mobile edge computing task unloading system has higher work efficiency;(2) The whole process model of mobile edge computing task unloading completed in this study can reduce the task processing delay in the actual use process;(3) The unloading system with intelligent algorithms is more suitable for edge devices, providing a reference task unloading model for engineering practice.

关键词： Compute task offloading edge devices intelligent algorithms mobile communications model system optimization

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intelligent algorithms in Orthodontic Diagnostics and Planning

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INFORMATIONEN AUS ORTHODONTIE UND KIEFERORTHOPAEDIE 2018年第3期50卷 191-197页

作者： Kuehnert, Tom Krey, Karl-Friedrich Image Instruments GmbH Niederwaldstr 3 D-09123 Chemnitz Germany Zentrum Zahn Mund & Kieferheilkunde Poliklin Kieferorthopadie Greifswald Germany

Zusammenfassung Algorithmen und Losungsstrategien aus dem Forschungsgebiet der Kunstlichen Intelligenz (KI) spielen eine wichtige Rolle in der zunehmend digitalen Verarbeitung in der modernen Kieferorthopadie. Im Artikel wird diskutiert, inwiefern die kieferorthopadische Behandlung von aktuellen Entwicklungen profitieren kann und wo Grenzen und Gefahren gesehen werden. Anhand von 3 Beispielen zur Verwendung digitaler Modelle in der Imaging-Software OnyxCeph(3) (Software OnyxCeph (3TM) , Image Instruments GmbH, Chemnitz. *** ) wird abgeleitet, welche Erwartungen an computergestutzte Diagnostik und Behandlung realistisch sind. Ziel des Artikels ist, dem Behandler Einblicke in den softwaretechnologischen Hintergrund zu geben, mit denen eine Erwartungshaltung an die KI begrundet werden kann, die sowohl patientengerecht als auch zukunftsorientiert ist. Abstract algorithms and approaches from the field of artificial intelligence play an important role in the increasingly digital workflows of modern orthodontics. This article discusses in which way the orthodontic treatment can benefit from current developments in this field and where to consider limitations and possible risks. Based on three examples of digital model processing from the imaging software OnyxCeph(3) (Software OnyxCeph (3TM) , Image Instruments GmbH, Chemnitz. *** ), we derive which expectations for computer-aided diagnostics and treatment are reasonable. Intention of the article is to inform the reader from a software engineering point of view, so that an anticipation of the capabilities of AI can be formed which fits both patient needs and future developments.

关键词： intelligent algorithms orthodontics virtual setup

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Natural Computing and intelligent algorithms in Materials Image Processing Technology

Natural Computing and Intelligent Algorithms in Materials Im...

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Conference on the Future Computer and Control Systems

作者： Zhang, Jing Beijing Union Univ Basic Courses Dept Beijing Peoples R China

ISBN: (纸本)9783642293894

intelligent algorithm is simulated biological theory of intelligent systems constitute a new type of information processing technology, has been widely used in industrial engineering, information processing and other fields. In recent years, in the field of image processing and analysis. intelligent algorithms are also widely used technology. In this paper, intelligent algorithm technique in medical image segmentation, image registration and the application of computer-aided technology and research are reviewed, representative described techniques and algorithms.

关键词： materials image processing intelligent algorithms information technology

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An Improved Temperature Prediction Technique for HVAC Units Using intelligent algorithms 11

An Improved Temperature Prediction Technique for HVAC Units ...

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11th Annual IEEE Energy Conversion Congress and Exposition (ECCE)

作者： Yan, Keming Diduch, Chris Kaye, Mary E. Univ New Brunswick Dept Elect & Comp Engn Fredericton NB Canada

ISBN: (纸本)9781728103952

This paper proposed a methodology to automatically search for the best combination of the Learning Horizon (LH) and Predicting Horizon (PH) with the objective of improving the prediction performance for a temperature prediction technique for HVAC units. Three intelligent algorithms, Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Greedy Algorithm (GRA), are integrated into a temperature prediction process for identifying the parameters of a thermodynamic model. The developed temperature prediction technique was tested, validated, and evaluated in a case study. This case study also compared the prediction performances of the three different optimization algorithms mentioned earlier and explored the impact of the LHs and PHs on the prediction performance. By setting up the selection standards for evaluating the prediction performances of the temperature prediction technique, the most suitable algorithm was then selected along with the best combination of the LH and PH.

关键词： indoor temperature prediction intelligent algorithms parameter optimization

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The Assessment Strategy for intelligent algorithms Using Improved Osculating Value Method 12

The Assessment Strategy for Intelligent Algorithms Using Imp...

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12th IEEE Int Conf Ubiquitous Intelligence & Comp/12th IEEE Int Conf Autonom & Trusted Comp/15th IEEE Int Conf Scalable Comp & Commun & Associated Workshops/IEEE Int Conf Cloud & Big Data Comp/IEEE Int Conf Internet People

作者： Dong, Xueshi Dong, Wenyong Wang, Yufeng Wuhan Univ Comp Sch Wuhan 430072 Hubei Peoples R China

ISBN: (纸本)9781467372114

During the past decades, dozens of intelligent algorithms (IAs), such as genetic algorithm (GA), ant colony algorithm (ACA), particle swarm optimization (PSO), emerge to solve complex optimal problems. But it is still an open problem to impartially and effectively evaluate their performances. A new assessment strategy for IAs based on improved osculating value method is firstly proposed to provide a solution for this problem. The idea of the osculating value method is that evaluation index is divided into positive and reverse index, then find out the most advantage and worst points for the evaluation index, the distance is calculated for each evaluation unit and the advantage and the worst points, the transformed distance as comprehensive index reflecting advantage and disadvantage of each sample is called close value, according to the close value, finally determine the order of each evaluation unit. The paper takes the GA and ACA for solving TSP as example, chooses solving time, algorithm complexity, solution accuracy and coding complexity as evaluation index system, it can assess algorithms from many perspectives, and avoid the disadvantage of traditional single index, by computing and analysis in certain experiment condition, it shows that ACA for TSP is better than GA.

关键词： improved osculating value method intelligent algorithms assessment method TSP

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Comparative Study of Several intelligent algorithms for Knapsack Problem

Comparative Study of Several Intelligent Algorithms for Knap...

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2nd International Conference on Challenges in Environmental Science and Computer Engineering (CESCE)

作者： Zhang, Jing Beijing Union Univ Basic Courses Dept Beijing Peoples R China

Knapsack problem in the field of combinatorial optimization is a typical, easy-to-describe but difficult to deal with NP-complete problems. Knapsack problem for large-scale, are not yet very effective way, how quickly and effectively solve the knapsack problem has important theoretical and practical significance, is widely used in engineering practice. We introduce the knapsack problem, discusses the current knapsack problem several intelligent algorithm is more effective (simulated annealing algorithm, ant colony algorithm, taboo search method), a simple illustration of their solution process, respectively, and pointed out their advantages and disadvantages the prospects for solving knapsack problem raised outlook. (C) 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of the intelligent Information Technology Application Research Association.

关键词： Knapsack problem intelligent algorithms simulated annealing ant colony algorithm taboo search

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Routing of vehicles by intelligent algorithms in the matter of transporting goods

Routing of vehicles by intelligent algorithms in the matter ...

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IEEE International Conference on Electrical Engineering, Big Data and algorithms (EEBDA)

作者： Raeesi, Hadi Hosseinpour, Amirhossein Golestan Univ Elect Engn Gorgan Golestan Iran

ISBN: (纸本)9781665416061

The task of route planning for a mobile robot or vehicle has attracted the attention of many research papers. In these writings, it is mostly assumed that the robot has a complete and accurate model of its surroundings before moving. Less attention has been paid to the issue of unknown environments. This is the case for a crawler or robot that has to move towards a target without a map of the area, such as vehicle route planning. Traditional intelligent Hard-NP optimization algorithms occur because this has been proven to be of the type they have not had much success in it. As a result, various innovative methods have been used to solve these problems. In the meantime, evolutionary methods are used as a population-based method with an increasing trend. On the other hand, for routing mobile robots, when the working space of the robot is clear, routing for the mobile robot is done in a global mode and offline. If the specifications of the environment are not known, routing is done locally and on the line by taking information from the sensors. In this research, the problem of routing a mobile robot in an unknown environment with two-dimensional dynamic barriers is addressed. Used off-line. Comparison and evaluation of the simulation results of the proposed evolutionary algorithms indicate that the robot guidance from the obtained path has the optimal criteria, in other words, the selected path length has the lowest cost and is much closer to the shortest possible path length.

关键词： vehicles Routing A* RRT RRT* intelligent algorithms path planning

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