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Construction and optimization of regional ecological security patterns based on MSPA-MCR-GA Model: A case study of Dongting Lake Basin in China

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ECOLOGICAL INDICATORS 2024年 165卷

作者： Chen, Wenhao Liu, Huimin Wang, Jinlong Cent South Univ Sch Geosci & Info Phys Changsha 410083 Peoples R China Cent South Univ Forestry & Technol Sch Business Changsha 410004 Peoples R China

Ecological security pattern (ESP) represents a sound spatial arrangement of ecosystem occurring in landscape. The research on the optimization of ESP aims to improve and restore the ecosystem functions by rationally allocating and optimizing the ecological elements based on the key ecological issues. Constructing and optimizing ESP can enhance the connectivity of regional habitat patches, which is of great significance for protecting and restoring biodiversity, improving ecosystem stability and resilience, and achieving regional sustainable development. However, it is a challenging task to systematically improve the connectivity and resilience of regional ecological networks under attacks. Little research has been done on enhancing the resilience of ecological networks under edge-based attacks. Based on morphological spatial pattern analysis (MSPA), minimum cumulative resistance (MCR) and greedy algorithm (GA) models, this study presents a new method to construct and optimize ESP. The Dongting Lake Basin in China, which is a typical region with rich biodiversity, complex landscape patterns, and intensive human activities, is taken as an example. The results indicate that the optimization of the ecological network has improved its connectivity by 51.62%, its robustness against random edge-based attacks by 41.13%, and its robustness against targeted edge-based attacks by 43.41%, relative to the initial ecological network. Monte Carlo test verifies the reliability of the optimization solution. The proposed method can be used for finding the network structure with the best robustness for specific edge-based attacks, and it provides valuable decision-making reference for ecological land planning and biodiversity conservation.

关键词： Ecological security pattern Morphological spatial pattern analysis Minimum cumulative resistance greedy algorithm Ecological networks

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Integrating Minimum Spanning Tree and MILP in Urban Planning: A Novel algorithmic Perspective

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BUILDINGS 2024年第1期14卷 213页

作者： Pavon, Wilson Torres, Myriam Inga, Esteban Univ Politecn Salesiana Engn Dept Quito 170525 Ecuador Univ Politecn Salesiana Architecture Dept Quito 170525 Ecuador Univ Politecn Salesiana Postgrad Dept Quito 170525 Ecuador

This paper presents a novel eight-step iterative algorithm for optimizing the layout of a neighborhood, focusing on the efficient allocation of houses to strategically placed facilities, herein referred to as 'points of interest'. The methodology integrates a mixed integer linear programming (MILP) approach with a heuristic algorithm to address a variant of the facility location problem combined with network design considerations. The algorithm begins by defining a set of geographic coordinates to represent houses within a predefined area. It then identifies key points of interest, forming the basis for subsequent connectivity and allocation analyses. The methodology's core involves applying the greedy algorithm to assign houses to the nearest points of interest, subject to capacity constraints. The method is followed by computing a Minimum Spanning Tree (MST) among these points to ensure efficient overall connectivity. The proposed algorithm's iterative design is a key attribute. The most promising result of this approach is its ability to minimize the distance between houses and points of interest while optimizing the network's total length. This dual optimization ensures a balanced distribution of houses and an efficient layout, making it particularly suitable for urban planning and infrastructure development. The paper's findings demonstrate the algorithm's effectiveness in creating a practical and efficient neighborhood layout, highlighting its potential application in large-scale urban planning and development projects.

关键词： urban planning optimization facility location problem heuristic algorithms Mixed Integer Linear Programming (MILP) Geographic Information Systems (GIS) Minimum Spanning Tree (MST) network design greedy algorithm spatial allocation infrastructure development

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Generalized hop-based approaches for identifying influential nodes in social networks

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EXPERT SYSTEMS 2024年第10期41卷

作者： Biswas, Tarun Kumer Abbasi, Alireza Chakrabortty, Ripon Kumar Univ New South Wales Sch Syst & Comp Canberra ACT 2610 Australia Jashore Univ Sci & Technol Dept Ind & Prod Engn Jashore Bangladesh

Locating a set of influential users within a social network, known as the Influence Maximization (IM) problem, can have significant implications for boosting the spread of positive information/news and curbing the spread of negative elements such as misinformation and disease. However, the traditional simulation-based spread computations under conventional diffusion models render existing algorithms inefficient in finding optimal solutions. In recent years, hop and path-based approaches have gained popularity, particularly under the cascade models to address the scalability issue. Nevertheless, these existing functions vary based on the considered hop-distance and provide no guidance on capturing spread sizes beyond two-hops. In this paper, we introduce Hop-based Expected Influence Maximization (HEIM), an approach utilizing generalized functions to compute influence spread across varying hop-distances in conventional diffusion models. We extend our investigation to the Linear Threshold (LT) model, in addition to the Independent Cascade (IC) and Weighted Cascade (WC) models, filling a gap in current literature. Our theoretical analysis shows that the proposed functions preserve both monotonicity and submodularity, and the proposed HEIM algorithm can achieve an approximation ratio of (1-1/e) under a limited hop-measures, whereas a multiplicative (1k(oh)(1e-k(oh))alpha)-approximation under global measures. Furthermore, we show that expected spread methods can serve as a better benchmark approach than existing simulation-based methods. The performance of the HEIM algorithm is evaluated through experiments on three real-world networks, and is compared to six other existing algorithms. Results demonstrate that the three-hop based HEIM algorithm achieves superior solution quality, ranking first in statistical tests, and is notably faster than existing benchmark approaches. Conversely, the one-hop-based HEIM offers faster computation while still delivering competitive solut

关键词： greedy algorithm Influence Maximization information diffusion social network analysis

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String Rearrangement Inequalities and a Total Order Between Primitive Words

String Rearrangement Inequalities and a Total Order Between ...

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3rd International Joint Conference on Theoretical Computer Science (IJTCS) / 16th International Conference on Frontiers of algorithmic Wisdom (FAW)

作者： Luo, Ruixi Zhu, Taikun Jin, Kai Sun Yat Sen Univ Sch Intelligent Syst Engn Shenzhen Campus Shenzhen Peoples R China

ISBN: (纸本)9783031207952;9783031207969

We study the following rearrangement problem: Given n words, rearrange and concatenate them so that the obtained string is lexicographically smallest (or largest, respectively). We show that this problem reduces to sorting the given words so that their repeating strings are non-decreasing (or non-increasing, respectively), where the repeating string of a word A refers to the infinite string AAA.... Moreover, for fixed size alphabet Sigma, we design an O(L) time sorting algorithm of the words (in the mentioned orders), where L denotes the total length of the input words. Hence we obtain an O(L) time algorithm for the rearrangement problem. Finally, we point out that comparing primitive words via comparing their repeating strings leads to a total order, which can further be extended to a total order on the finite words (or all words).

关键词： String rearrangement inequalities Primitive words Combinatorics on words String ordering greedy algorithm

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On the interpretability of fuzzy knowledge base systems

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PEERJ COMPUTER SCIENCE 2024年 10卷 e2558-e2558页

作者： Camastra, Francesco Ciaramella, Angelo Salvi, Giuseppe Sposato, Salvatore Staiano, Antonino Univ Napoli Parthenope Dipartimento Sci & Tecnol Naples Italy Univ Napoli Parthenope Sci Econ Giurid Informat & Motorie Nola Italy

In recent years, fuzzy rule-based systems have been attracting great interest in interpretable and eXplainable Artificial Intelligence as ante-hoc methods. These systems represent knowledge that humans can easily understand, but since they are not interpretable per se , they must remain simple and understandable, and the rule base must have a compactness property. This article presents an algorithm for minimizing the fuzzy rule base, leveraging rough set theory and a greedy strategy. Reducing fuzzy rules simplifies the rule base, facilitating the construction of interpretable inference systems such as decision support and recommendation systems. Validation and comparison of the proposed methodology using both real and benchmark data yield encouraging results.

关键词： greedy algorithm Interpretabile and explainable artificial intelligence NP-hard problem Fuzzy knowledge base Rough set theory

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A comparison of matching algorithms for kidney exchange programs addressing waiting time

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CENTRAL EUROPEAN JOURNAL OF OPERATIONS RESEARCH 2021年第2期29卷 539-552页

作者： Monteiro, Tiago Klimentova, Xenia Pedroso, Joao Pedro Viana, Ana INESC TEC Porto Portugal Univ Porto Fac Ciencias Porto Portugal Polytech Porto ISEP Sch Engn Porto Portugal

Kidney exchange programs (KEP) allow an incompatible patient-donor pair, whose donor cannot provide a kidney to the respective patient, to have a transplant exchange with another in a similar situation if there is compatibility. Exchanges can be performed via cycles or chains initiated by non-directed donors (NDD), i.e., donors that do not have an associated patient. The objective for optimization in KEP is generally to maximize the number of possible transplants. Following the course of recent approaches that consider a dynamic matching (exchanges are decided every time a pair or a NDD joins the pool), in this paper we explore two matching policies to find feasible exchanges: periodic, where the algorithm runs within some period (e.g each 3 month);and greedy, in which a matching run is done as soon as the pool is updated with a new pair or NDD. For each policy, we propose a matching algorithm that addresses the waiting times of pairs in a pool. We conduct computational experiments with the proposed algorithms and compare the results with those obtained when periodic and greedy matching aim at maximizing the number of transplants.

关键词： Kidney exchange programs Simulation greedy algorithm Waiting time

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Modeling research of satellite-to-ground quantum key distribution constellations

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ACTA ASTRONAUTICA 2021年 180卷 470-481页

作者： Wang, Junyong Chen, Hongyu Zhu, Zhencai Chinese Acad Sci Innovat Acad Microsatellites Shanghai 201203 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China ShanghaiTech Univ Sch Informat Sci & Technol Shanghai 201210 Peoples R China

Satellite-based quantum key distribution is the key to develop the intercontinental quantum network. After the demonstrations by Chinese satellite Micius, the prospect of global-scale quantum internet is no more out of reach. However, the research efforts on modeling of constellation of quantum satellite is still insufficient so far. In this paper, we study the algorithm to select quantum key distribution access, the key size re-distribution optimization model and corresponding key size consumption along inter-satellite links. Besides, we present the brief discussion of how the constellation configuration interferes quantum key distribution performance.

关键词： Quantum key distribution Satellite constellation Low Earth orbit greedy algorithm Trusted node Inter-satellite link

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A randomized algorithm for joint power and channel allocation in 5G D2D communication

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COMPUTER COMMUNICATIONS 2021年 179卷 22-34页

作者： Ghosal, Subhankar Ghosh, Sasthi C. Indian Stat Inst Adv Comp & Microelect Unit Kolkata 700108 India

We formulate the joint power and channel allocation problem (JPCAP) for device to device (D2D) communication as a cost minimization problem, where cost is defined as a linear combination of the number of channels used and total power requirement. We first show that JPCAP is a NP-hard problem and providing n(1/epsilon) approximation for JPCAP for all epsilon > 0 is also NP-hard. Then we propose a mixed integer linear programming (MILP) to solve this problem. As solving MILP is a NP-hard problem we propose a greedy channel and power allocation (GCPA) algorithm to assign channels and powers to the links. We design GCPA in such a fashion that there exists an order of the links for which it produces optimum solution. We show that an order is equivalent to many orders and hence design an incremental algorithm (IA) to efficiently search good orders. Finally using IA we develop a randomized joint channel and power allocation (RJCPA) algorithm. We show that if a certain condition holds we can find the optimum in expected polynomial time else a slowly growing exponential time with very high probability. We then theoretically calculate the expected cost and energy efficiency (EE) produced by RJCPA. Through simulation, we show that RJCPA outperforms two existing approaches with respect to both cost and EE significantly. Finally we validate our theoretical findings through simulation.

关键词： 5G D2D communication Joint channel and power allocation Energy efficiency greedy algorithm Randomized algorithm Expected cost

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Integrative approach for transducer positioning optimization for ultrasonic structural health monitoring for the detection of deterministic and probabilistic damage location

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STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL 2021年第3期20卷 1117-1144页

作者： Ewald, Vincentius Groves, Roger Benedictus, Rinze Delft Univ Technol Fac Aerosp Engn Aerosp NDT Lab Kluyverweg 1 NL-2629 HS Delft Netherlands Delft Univ Technol Fac Aerosp Engn Struct Integr & Composites Delft Netherlands

The concept of structural health monitoring has been introduced to ensure structural integrity during the design lifetime of a structure. The main objectives of structural health monitoring are to detect, locate, quantify, and predict any damage that occurs during this lifetime of the structure so that effective and efficient maintenance and repair procedures can be performed. The location of structural damage events can be discretized as deterministic and probabilistic. A deterministic location specifies that the damage occurs in high-stress regions or other regions that can be predicted by the structural design, such as the most probable location for a fatigue crack. A probabilistic damage event is one where the location of the damage is independent of structural design parameters, such as hail impact, bird strike, and impact from ground vehicles. A structural health monitoring system should be able to handle both these damage occurrences. In our previous work, we optimized the transducer placement in Lamb wave-based structural health monitoring for the detection of a fatigue crack that emerges from a rivet hole. In this article, we demonstrate a combination of that method with a different sensor placement optimization method to add the capability to detect probabilistic damage location. First, we considered the ultrasonic wave attenuation in the structure and based on this attenuation, we created a fitness function. Since this fitness function is difficult to solve due to its combinatorial nature, we compared three common metaheuristic stochastic strategies: global random search, greedy algorithm, and genetic algorithm, for solving this problem. The results of this analysis were then integrated with the previously described deterministic approach, making a global structural health monitoring sensor placement strategy that balances the need to detect both pre-determined and random damage location occurrences. The analytical result of the study presented is validat

关键词： Ultrasonic structural health monitoring sensor placement option fatigue crack impact damage metaheuristic search random search greedy algorithm genetic algorithm

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Clustered Discriminant Regression for High-Dimensional Data Feature Extraction and Its Applications in Healthcare and Additive Manufacturing

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IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2021年第4期18卷 1998-2010页

作者： Shen, Bo Xie, Weijun James Kong, Zhenyu Virginia Tech Grado Dept Ind & Syst Engn Blacksburg VA 24061 USA

The recent increase in applications of high-dimensional data poses a severe challenge to data analytics, such as supervised classification, particularly for online applications. To tackle this challenge, efficient and effective methods for feature extraction are critical to the performance of classification analysis. The objective of this work is to develop a new supervised feature extraction method for high-dimensional data. It is achieved by developing a clustered discriminant regression (CDR) to extract informative and discriminant features for high-dimensional data. In CDR, the variables are clustered into different groups or subspaces, within which feature extraction is performed separately. The CDR algorithm, which is a greedy approach, is implemented to obtain the solution toward optimal feature extraction. One numerical study is performed to demonstrate the performance of the proposed method for variable selection. Three case studies using healthcare and additive manufacturing data sets are accomplished to demonstrate the classification performance of the proposed methods for real-world applications. The results clearly show that the proposed method is superior over the existing method for high-dimensional data feature extraction. Note to Practitioners-This article forwards a new supervised feature extraction method termed clustered discriminant regression. This method is highly effective for classification analysis of high-dimensional data, such as images or videos, where the number of variables is much larger than the number of samples. In our case studies on healthcare and additive manufacturing, the performance of classification analysis based on our method is superior over the existing feature extraction methods, which is confirmed by using various popular classification algorithms. For image classification, our method with elaborately selected classification algorithms can outperform a convolutional neural network. In addition, the computation efficien

关键词： Feature extraction Medical services Three-dimensional printing Data mining Clustering algorithms Monitoring Input variables Additive manufacturing (AM) classification analysis clustering discriminant regression (DR) greedy algorithm healthcare variable selection

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