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BACKWARD FUZZY heuristic-search algorithm FBHAO-ASTERISK FOR FUZZY GENERAL AND/OR GRAPH

FUZZY SETS AND SYSTEMS 1993年第1期60卷 67-75页

作者： WANG, ST CHEN, JF Department of Computer Zhenjiang Shipbuilding Institute Zhengjiang Jiangsu China

In this paper, a new kind of fuzzy general and/or graph is defined on a continuous triangular norm and its extension. In terms of the newly-defined heuristic function ($) over tilde h(n,x) and the principle that all subtrees of the optimal solution tree for fuzzy general and/or graph are also optimal solution trees, the Backward Fuzzy heuristic search algorithm FBHAO* for the fuzzy general And/Or graph is presented, and its admissibility is proved. Furthermore, two new concepts of monotone restriction for heuristic function ($) over tilde h(n,x) are designed. Based on those, the property of monotone restrictions for algorithm FBHAO* is investigated, and the comparison between two algorithms FBHAO* is discussed.

关键词： GRAPH THEORY ARTIFICIAL INTELLIGENCE TRIANGULAR NORM FUZZY SETS heuristic search algorithm

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An Efficient Network IDS for Cloud Environments Based on a Combination of Deep Learning and an Optimized Self-adaptive heuristic search algorithm 7th

An Efficient Network IDS for Cloud Environments Based on a C...

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7th International Conference on Networked Systems (NETYS)

作者： Chiba, Zouhair Abghour, Noreddine Moussaid, Khalid El Omri, Amina Rida, Mohamed Hassan II Univ Casablanca Fac Sci Ain Chock LIMSAD Labs Casablanca 20100 Morocco

ISBN: (纸本)9783030312770;9783030312763

Nowadays, Cloud Computing (CC) is one of the fastest emerging core technologies in the current information era. It is leading a new revolution on the ways of data storage and calculation. CC remains gaining traction among organizations thanks to its appealing features like pay-per-use model for billing customers, elasticity, ubiquity, scalability and availability of resources for businesses. Hence, many organizations are moving their workloads or processes to cloud due to its inherent advantages. Nevertheless, several security issues arise with the transition to this computing paradigm including intrusion detection. Attackers and intruders developed new sophisticated tools defeating traditional Intrusion Detection Systems (IDS) by huge amount of network traffic data and dynamic behaviors. The existing Cloud IDSs suffer from low detection accuracy and high false positive rate. To overcome this issue, we propose a smart approach using a self-adaptive heuristic search algorithm called "Improved Self-Adaptive Genetic algorithm" (ISAGA) to build automatically a Deep Neural Network (DNN) based Anomaly Network Intrusion Detection System (ANIDS). ISAGA is a variant of standard Genetic algorithm (GA), which is developed based on GA improved through an Adaptive Mutation algorithm (AMA) and optimization strategies. The optimization strategies carried out are Parallel Processing and Fitness Value Hashing that reduce execution time, convergence time and save processing power. Our approach consists of using ISAGA with the goal of searching the optimal or near optimal combination of most relevant values of the parameters included in construction of DNN based IDS or impacting its performance, like feature selection, data normalization, architecture of DNN, activation function, learning rate and Momentum term, which ensure high detection rate, high accuracy and low false alarm rate. CloudSim 4.0 simulator platform and CICIDS2017 dataset were used for simulation and validation of the

关键词： Cloud computing Anomaly detection Network intrusion detection system Deep Neural Network Optimization Genetic algorithm Adaptive Mutation algorithm heuristic search algorithm Parallel processing Fitness value hashing CICIDS2017 dataset

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Load Balancing in Distribution System Using heuristic search algorithm

Load Balancing in Distribution System Using Heuristic Search...

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International Conference on Advances in Sustainable Engineering and its Application (ICASEA)

作者： Handhal, Fadhela K. Rashid, Abdulmuttalib T. Univ Basrah Elect Engn Dept Basrah Iraq

ISBN: (纸本)9781538635407

With the increasing use of technology and automation in various fields of modern life, the electrical outage has become a major impact to complete the requirements in the daily life of most sectors like industrial, economic and even recreational. It is, therefore, necessary to have access to a reliable electrical system to ensure continuity of consumer electric consumption. Based on the above, the heuristic searching algorithm is proposed for loads balancing in an unbalanced electrical distribution network. The imbalance ratio was calculated for the network chosen for study. The heuristic algorithm is programmed using values represent the three-phase currents of 20 houses. Each house assumes to have a smart energy meter connected with some contactors used for current balancing by phases swapping. Three cases are programmed using the heuristic algorithm to study the effect of used different numbers of contactors in each house. All the cases show high performance in loads balancing and reduced the imbalance index.

关键词： load balancing heuristic search algorithm electrical distribution network imbalance index

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A heuristic search algorithm for vehicle routing problems and the GIS-based vehicle routing system onboard

A heuristic search algorithm for vehicle routing problems an...

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13th International Conference on Management Science and Engineering

作者： Li Yong-xian Hu Xiang-pei Lu Jun Dalian Univ Technol Inst Syst Engn Dalian 116023 Peoples R China

ISBN: (纸本)7560323553

Focusing on a specific vehicle routing problem that is used in onboard and embedded equipments and incorporates road condition and its change, traffic rules and several different destinations, this paper divides the vehicle routing problem into two parts, local routing and global routing, describes the heuristic search algorithm for routing problems onboard, and defines evaluation functions for local routing and global routing respectively. Embedded development platform-eSuperMap is applied to the construction of vehicle routing system and key techniques of the system are researched. Furthermore, based on embedded GIS, the vehicle routing system is designed and realized.

关键词： vehicle routing problem heuristic search algorithm embedded development component GIS

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A block-based heuristic search algorithm for the two-dimensional guillotine strip packing problem

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ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 2024年 134卷

作者： Zhang, Hao Yao, Shaowen Zhang, Shenghui Leng, Jiewu Wei, Lijun Liu, Qiang Guangdong Univ Technol Guangdong Prov Key Lab Comp Integrated Mfg Syst State Key Lab Precis Elect Mfg Technol & Equipment Guangzhou 510006 Peoples R China

Introduction: This paper addresses the two-dimensional strip -packing (2DSP) problem of placing a set of rectangular pieces onto a fixed -width rectangular sheet to minimize the total length used. Methodology: We propose a Block -Based heuristic search algorithm (BBHSA) to solve 2DSP problems with guillotine cut constraints. Initially, it converts the 2DSP problem into a series of 2D rectangular packing problems (2DRP), where the size of the sheet is fixed. In the BBHSA, rectangular pieces are aggregated into blocks, which are partial solutions without residual space. These blocks provide the ingredients for a good layout and are basic components in a tree -based constructive search process. Two basic operations, called placing & splitting and approximate binary search are used in the search process. Furthermore, several block -based placement rules are explored to speed up the search process and improve solution quality. Result discussion: To verify the performance of our proposed algorithm, we conducted extensive experiments using the zero -waste benchmark and non -zero -waste benchmark instances. Final results: The results show that BBHSA demonstrates computational effectiveness, particularly in zerowaste cases, achieving optimal solutions for almost all zero -waste benchmark instances reported in the existing literature.

关键词： Packing Two-dimensional strip-packing Block Guillotine cut heuristic search algorithm

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Efficient and cost-effective method for identifying urban ventilation corridors using a heuristic search algorithm

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Sustainable Cities and Society 2024年 101卷

作者： Lau, Tsz-Kin Tsai, Pei-Chi Ou, Hsing-Yu Lin, Tzu-Ping Department of Architecture National Cheng Kung University 1 University Rd. East Dist. Tainan 701 Taiwan

Global temperatures are rapidly increasing, and one of the consequences of such increases is the urban heat island effect, which is a major problem. Enhancing urban ventilation is a key strategy for reducing urban temperatures. This study proposes a method for efficiently identifying urban ventilation corridors. Taichung City in central Taiwan was selected as the study area, and remote sensing technologies were used to observe and extract the urban building information in two sites. The collected information was used to develop maps of the roughness length (z₀) in the city, and a heuristic search algorithm (A* search algorithm) was used to identify the urban ventilation corridors in the two sites and Taichung City overall. The results revealed that the remote sensing technologies were both accurate and cost-effective in obtaining building information, and the identified ventilation corridors were also accurate and exhibited higher-than-average wind speeds. Hence, the proposed method can be used to inexpensively and conveniently identify both corridors with high ventilation potential and poor ventilation that require urgent improvement. The method was further applied to identify ventilation corridors in the entirety of Taichung City, demonstrating the suitability of the proposed method for larger-scale applications. © 2023

关键词： heuristic search algorithm Sustainability Urban ventilation Ventilation corridors

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Iterative-deepening fuzzy heuristic search algorithms and their learning investigation

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FUZZY SETS AND SYSTEMS 1996年第3期82卷 351-355页

作者： Wang, ST Dept. Computer Zhenjiang Shipbuilding Institute Zhenjiang Jiangsu People's Republic of China

This paper presents a fuzzy, heuristic search algorithm FIDA* that applies iterative-deepening methods and dynamic modification of the heuristic function. It then improves the FIDA* algorithm by incorporating methods to propagate the modified heuristic function, (h) over tilde(n). It is pointed out that the algorithm FIDA* can be applied to learn over repeated uses on problems with the same state space and goal node. This paper presents a learning algorithm, LFIDA*, that overcomes difficulties that often occur in designing (h) over tilde(n).

关键词： fuzzy set theory heuristic search algorithm machine learning artificial intelligence

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Application of heuristic algorithm to Computer Based Interlocking Route search

Application of Heuristic Algorithm to Computer Based Interlo...

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2017 2nd International Conference on Control, Automation and Artificial Intelligence(CAAI2017)

作者： Li Ding Shenghua Dai School of Electronic and Information Engineering Beijing Jiaotong University

ISBN: (纸本)9781510845541

In the Computer Based Interlocking(CBI) System of railway stations, the route search sub-module is one of the most important components, since its operating efficiency, reliability and safety can directly ensure the safety of train routes and shunting routes. This paper took an actual layout of railway station signal into consideration. By means of modeling the layout into a topological structure, we abstracted it as a directed *** under the direction of path search in graph theory, we applied A* heuristic search algorithm to carry out the route search and it worked efficiently.

关键词： computer based interlocking route search heuristic search algorithm

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A Bidirectional heuristic search for web service composition with costs

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INTERNATIONAL JOURNAL OF WEB AND GRID SERVICES 2010年第2期6卷 160-175页

作者： Ukey, Nilesh Niyogi, Rajdeep Singh, Kuldip Milani, Alfredo Poggioni, Valentina Indian Inst Technol Roorkee Dept Elect & Comp Engn Roorkee 247667 Uttar Pradesh India Univ Perugia Dept Math & Comp Sci I-06100 Perugia Italy

This paper presents a model for web service composition based on navigating the web service dependency graph by bidirectional heuristic algorithm. The algorithm is based on a new domain-independent heuristic, while a cost optimisation strategy that balances optimality and convergence performance is also proposed. Experiments on different types of dependency graphs of varying sizes and number of web services show promising results for the service composition model when compared with state-of-the-art search algorithms. The proposed dependency-graph-based composition model can be extended to more general frameworks such as collective systems and virtual environments where a plurality of agents interact composing different actions, services, or resources.

关键词： web service composition dependency graph heuristic search algorithm

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A Bird Flock Gravitational search algorithm Based on the Collective Response of Birds

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COMPUTER JOURNAL 2017年第11期60卷 1687-1716页

作者： Han, XiaoHong Qiang, Yan Lan, Yuan Taiyuan Univ Technol Minist Educ China Key Lab Adv Transducers & Intelligent Control Sys Taiyuan Shanxi Peoples R China

Gravitational search algorithm (GSA) is a stochastic search algorithm based on the law of gravity and mass which is widely used nowadays for efficient solution of optimization problems. For the purpose of enhancing the performance of original GSA, this paper proposes a new GSA called Bird Flock Gravitational search algorithm (BFGSA) based on the collective response of birds. Although GSA performs well in many problems, algorithms in this category lack mechanisms which add diversity to exploration in the search process. Our proposed algorithm introduces a new mechanism into GSA to add diversity, a mechanism which is inspired by the collective response behavior of birds. This mechanism performs its diversity enhancement through three main major steps including initialization, identification of the nearest neighbors and orientation change. The initialization is to generate candidate populations for the second steps and the orientation change updates the position of objects based on the nearest neighbors. Due to the collective response mechanism, the BFGSA explores a wider range of the search space and thus escapes suboptimal solutions. The efficiency and robustness of the proposed algorithm is demonstrated using multiple traditional and newly composed benchmark functions presented in CEC2005 competition and the results are compared with recent variants of the original particle swarm optimization and state-of-the-art GSA algorithms. Furthermore, we applied BFGSA to a real-world application of data clustering. The results show that BFGSA improves the performance of the original GSA and obtains the best results compared with our selected GSA-type algorithms in benchmarking experiments and clustering experiments.

关键词： gravitational search algorithm learning algorithm heuristic search algorithm collective behavior numerical function optimization data clustering

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