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EvoCluster: An Open-Source Nature-Inspired Optimization Clustering Framework

Raneem Qaddoura, Hossam Faris, Ibrahim Aljarah, Pedro A. Castillo
2021 SN Computer Science  
This paper is an extension to the existing EvoCluster framework in which it includes different distance measures for the objective function, different techniques of detecting the k value, and a user option  ...  The current implementation of the framework includes ten metaheuristic optimizers, thirty datasets, five objective functions, twelve evaluation measures, more than twenty distance measures, and ten different  ...  Declarations Conflict of interest The authors declare that they have no conflict of interest.  ... 
doi:10.1007/s42979-021-00511-0 fatcat:vj3gec5qxncptmrwzumo7hvore

Fail-stop Failure Recovery in Neighbor Replica Environment

Ahmad Shukri Mohd Noor, Mustafa Mat Deris
2013 Procedia Computer Science  
This paper propose a resource manager for optimal resource selection.  ...  This model utilized the advantages of the distributed neighbor replica technique (NRT). In this paper, the algorithm along with theoretical framework for autonomous failure recovery are illustrated.  ...  We present the algorithm along with theoretical framework for autonomous failure recovery are illustrated. We propose a resource manager for optimal resource selection.  ... 
doi:10.1016/j.procs.2013.06.145 fatcat:pl6722rblbglzcwkkuy43ve4je

Automatic Data Clustering Framework Using Nature-Inspired Binary Optimization Algorithms

Behnaz Merikhi, M. R. Soleymani
2021 IEEE Access  
A wide range of binary optimization algorithms can be utilized for the optimizer.  ...  Then, in [42] , Kuo and Zulvia proposed a hybrid solution of an improved artificial bee colony optimization and K-means algorithm called iABC for the automatic clustering problem and the customer segmentation  ... 
doi:10.1109/access.2021.3091397 fatcat:dqkhxi6yuvb67ll5j42bsc7mqy

Automatic Clustering Using a Synergy of Genetic Algorithm and Multi-objective Differential Evolution [chapter]

Debarati Kundu, Kaushik Suresh, Sayan Ghosh, Swagatam Das, Ajith Abraham, Youakim Badr
2009 Lecture Notes in Computer Science  
This paper applies the Differential Evolution (DE) and Genetic Algorithm (GA) to the task of automatic fuzzy clustering in a Multi-objective Optimization (MO) framework.  ...  It compares the performance a hybrid of the GA and DE (GADE) algorithms over the fuzzy clustering problem, where two conflicting fuzzy validity indices are simultaneously optimized.  ...  Introduction Optimization-based automatic clustering algorithms greatly rely on a cluster validity function (optimization criterion) the optima of which appear as proxies for the unknown "correct classification  ... 
doi:10.1007/978-3-642-02319-4_21 fatcat:6xkrm4w37jgy3mizapzwmrcq4e

ARLO: A Framework for Automated Reinforcement Learning [article]

Marco Mussi, Davide Lombarda, Alberto Maria Metelli, Francesco Trovò, Marcello Restelli
2022 arXiv   pre-print
In this work, we propose a general and flexible framework, namely ARLO: Automated Reinforcement Learning Optimizer, to construct automated pipelines for AutoRL.  ...  We also showcase the full pipeline on a realistic dam environment, automatically performing the feature selection and the model generation tasks.  ...  For each stage, we define its goal, performance index for tunable or automatic units, and implementation selected from the state-of-the-art methodologies.  ... 
arXiv:2205.10416v1 fatcat:i3ugqiwo3fcf5d7kgyg2xcmybi

There is No Such Thing as an "Index"! or: The next 500 Indexing Papers [article]

Jens Dittrich, Joris Nix, Christian Schön
2021 arXiv   pre-print
Based on that framework we propose a generic genetic index generation algorithm that, given a workload and an optimization goal, can automatically assemble and mutate, in other words 'breed' new index  ...  We present a new automatic index breeding framework coined Genetic Generic Generation of Index Structures (GENE).  ...  It neither details how traditional operators can be split nor how this can be turned into an optimization problem for automatic index creation. We fill that gap. Index Selection.  ... 
arXiv:2009.10669v2 fatcat:pr3ogonyyzdl3f2miteqhj46nu

Optimal Feature Point Selection and Automatic Initialization in Active Shape Model Search [chapter]

Karim Lekadir, Guang-Zhong Yang
2008 Lecture Notes in Computer Science  
The A* graph search algorithm is adapted to identify in the image the optimal set of valid feature points.  ...  This paper presents a novel approach for robust and fully automatic segmentation with active shape model search.  ...  For this purpose, a tree search algorithm based on the A* algorithm [9] is introduced for optimal feature point selection.  ... 
doi:10.1007/978-3-540-85988-8_52 fatcat:zt7xk32vinfvxgjbr7vjgtwq4q

XuanYuan: An AI-Native Database

Guoliang Li, Xuanhe Zhou, Sihao Li
2019 IEEE Data Engineering Bulletin  
Firstly, the traditional empirical optimization techniques (e.g., cost estimation, join order selection, knob tuning) cannot meet the high-performance requirement for large-scale data, various applications  ...  We also take autonomous database knob tuning, deep reinforcement learning based optimizer, machine-learning based cardinality estimation, and autonomous index/view advisor as examples to showcase the superiority  ...  self-assembling, but also provides in-database AI capabilities to lower the burden of using AI.  ... 
dblp:journals/debu/0001ZL19 fatcat:pdulbqa33jhjxeeqsisqwol6hu

The Algorithm for Algorithms: An Evolutionary Algorithm Based on Automatic Designing of Genetic Operators

Dazhi Jiang, Zhun Fan
2015 Mathematical Problems in Engineering  
At present there is a wide range of evolutionary algorithms available to researchers and practitioners.  ...  The results show that the proposed algorithm can outperform standard differential evolution algorithm in terms of convergence speed and solution accuracy which shows that the algorithm designed automatically  ...  Acknowledgments The authors would like to thank the anonymous reviewers for their very detailed and helpful comments that help us to increase the quality of this work.  ... 
doi:10.1155/2015/474805 fatcat:uzgqpw5bejhifndyrtoxsao3e4

K-Means-Based Nature-Inspired Metaheuristic Algorithms for Automatic Data Clustering Problems: Recent Advances and Future Directions

Abiodun M. Ikotun, Mubarak S. Almutari, Absalom E. Ezugwu
2021 Applied Sciences  
A quest approach for article selection was adopted, which led to the identification and selection of 147 related studies from different reputable academic avenues and databases.  ...  and serves as a comprehensive source of information regarding the K-means algorithm and its variants for the research community.  ...  [34] Allocating a range of values for k (between 2 and 10) and selecting the best value that produced the optimal solution Mustafi and Sahoo [36] Combining GA framework with differential evolution  ... 
doi:10.3390/app112311246 fatcat:i2q7267qcrgxnfsexl2ftp55qm

Algorithm Selection Based on a Region Similarity Metric for Intracellular Image Segmentation [chapter]

Satoko Takemoto, Hideo Yokot
2011 Image Segmentation  
Fig. 2 . 2 A framework of algorithm selection.  ...  An appropriate algorithm with an optimized parameter setting for each task is automatically selected according to unique evaluation metrics of algorithm performance.  ...  Algorithm Selection Based on a Region Similarity Metric for Intracellular Image Segmentation, Image Segmentation, Dr.  ... 
doi:10.5772/15807 fatcat:yrhojmlnczfgde553tbywykivu

A LASER-SLAM ALGORITHM FOR INDOOR MOBILE MAPPING

Wenjun Zhang, Qiao Zhang, Kai Sun, Sheng Guo
2016 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
The tree structure of sub-map can be indexed quickly and reduce the amount of memory consuming when mapping. The algorithm combined Bayes-based and graph optimization-based SLAM algorithm.  ...  It created virtual landmarks automatically by associating data of sub-maps for graph optimization.  ...  The circles is four automatic landmarks Optimization strategy: In order to ensure the correctness of the result, we designed two sets of optimization strategies for automatic optimization and manual  ... 
doi:10.5194/isprs-archives-xli-b4-351-2016 fatcat:jpeogaiwnfdxzleiic3ozssr3a

A LASER-SLAM ALGORITHM FOR INDOOR MOBILE MAPPING

Wenjun Zhang, Qiao Zhang, Kai Sun, Sheng Guo
2016 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
The tree structure of sub-map can be indexed quickly and reduce the amount of memory consuming when mapping. The algorithm combined Bayes-based and graph optimization-based SLAM algorithm.  ...  It created virtual landmarks automatically by associating data of sub-maps for graph optimization.  ...  The circles is four automatic landmarks Optimization strategy: In order to ensure the correctness of the result, we designed two sets of optimization strategies for automatic optimization and manual  ... 
doi:10.5194/isprsarchives-xli-b4-351-2016 fatcat:4packjk3x5fdph7kt6k3htm34y

An Optimized Framework for Surgical Team Selection

Hemant Petwal, Rinkle Rani
2021 Computers Materials & Continua  
In this paper, we addressed the challenges of surgical team selection faced by a multispecialty hospital and proposed a decision-making framework for selecting the optimal list of surgical teams for a  ...  For this end, two population-based meta-heuristic algorithms for clustering of mixed datasets and multi-objective optimization were proposed.  ...  A recent study utilized k-prototypes algorithm for partitioning of patients and genetic algorithm (GA) for the selection of optimal surgical team [5] .  ... 
doi:10.32604/cmc.2021.017548 fatcat:my3mn5m5rrdihikorlamgzojyy

Index and Materialized View Selection in Data Warehouses [article]

Kamel Aouiche
2017 arXiv   pre-print
The aim of this article is to present an overview of the major families of state-of-the-art index and materialized view selection methods, and to discuss the issues and future trends in data warehouse  ...  We particularly focus on data mining-based heuristics we developed to reduce the selection problem complexity and target the most pertinent candidate indexes and materialized views.  ...  of indexes and views should be built automatically;  generic: the selection strategy should not be dependent on a particular DBMS;  modular: the selection strategy should be composed of independent  ... 
arXiv:1701.08029v1 fatcat:76g5f2g35fbyjiyy4lnm5ad7sa
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