A novel krill herd algorithm with orthogonality and its application to data clustering

2021 ◽  
Vol 25 (3) ◽  
pp. 605-626
Author(s):  
Chen Zhao ◽  
Zhongxin Liu ◽  
Zengqiang Chen ◽  
Yao Ning
Keyword(s):  
Data Clustering ◽  
Historical Data ◽  
Improved Method ◽  
Local Optima ◽  
Krill Herd Algorithm ◽  
Krill Herd ◽  
Promising Solution ◽  
First Time ◽  
Clustering Problems ◽  
Orthogonal Learning

Krill herd algorithm (KHA) is an emerging nature-inspired approach that has been successfully applied to optimization. However, KHA may get stuck into local optima owing to its poor exploitation. In this paper, the orthogonal learning (OL) mechanism is incorporated to enhance the performance of KHA for the first time, then an improved method named orthogonal krill herd algorithm (OKHA) is obtained. Compared with the existing hybridizations of KHA, OKHA could discover more useful information from historical data and construct a more promising solution. The proposed algorithm is applied to solve CEC2017 numerical problems, and its robustness is verified based on the simulation results. Moreover, OKHA is applied to tackle data clustering problems selected from the UCI Machine Learning Repository. The experimental results illustrate that OKHA is superior to or at least competitive with other representative clustering techniques.

scholarly journals Data Clustering Using Moth-Flame Optimization Algorithm

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4086
Author(s):  
Tribhuvan Singh ◽  
Nitin Saxena ◽  
Manju Khurana ◽  
Dilbag Singh ◽  
Mohamed Abdalla ◽  
...  
Keyword(s):  
Data Clustering ◽  
Research Work ◽  
Local Optima ◽  
Suggested Approach ◽  
Wide Range ◽  
Benchmark Datasets ◽  
The Mean ◽  
Moth Flame Optimization Algorithm ◽  
Clustering Problems ◽  
State Of Art

A k-means algorithm is a method for clustering that has already gained a wide range of acceptability. However, its performance extremely depends on the opening cluster centers. Besides, due to weak exploration capability, it is easily stuck at local optima. Recently, a new metaheuristic called Moth Flame Optimizer (MFO) is proposed to handle complex problems. MFO simulates the moths intelligence, known as transverse orientation, used to navigate in nature. In various research work, the performance of MFO is found quite satisfactory. This paper suggests a novel heuristic approach based on the MFO to solve data clustering problems. To validate the competitiveness of the proposed approach, various experiments have been conducted using Shape and UCI benchmark datasets. The proposed approach is compared with five state-of-art algorithms over twelve datasets. The mean performance of the proposed algorithm is superior on 10 datasets and comparable in remaining two datasets. The analysis of experimental results confirms the efficacy of the suggested approach.

Chaotic Tornadogenesis Optimization Algorithm for Data Clustering Problems

2018 ◽  
Vol 10 (1) ◽  
pp. 38-64 ◽  
Author(s):  
Ravi Kumar Saidala ◽  
Nagaraju Devarakonda
Keyword(s):  
Optimization Algorithm ◽  
Data Clustering ◽  
Optimal Number ◽  
Mathematical Functions ◽  
Local Optima ◽  
Internal Parameters ◽  
Data Clusters ◽  
Np Hard Problem ◽  
Clustering Problems ◽  
Optimal Number Of Clusters

This article describes how clustering is an attractive and major task in data mining in which particular set of objects are grouped according to their similarities based on some criteria. Among the numerous algorithms, k-Means is the best and efficient in address clustering problems. Any expert system is said to be good, only if it returns the optimal data clusters. The challenge of optimal clustering lies in finding the optimal number of clusters and identifying all the data groups correctly which is a NP-hard problem. Recently a new optimization algorithm TOA was developed to address these problems. However, the standard TOA is too often trapped at the local optima and premature convergence. To overcome this, this article proposes CTOA. The main objective of embedding chaotic maps into standard TOA is to compute and automatically adapt the internal parameters. The proposed CTOA is first benchmarked on standard mathematical functions and later applied to 10 data clustering problems. The obtained graphical and statistical results along with comparisons illustrate the capabilities of CTOA regarding accuracy and robustness

Bonobos

2018 ◽  
Keyword(s):  
19Th Century ◽  
Historical Data ◽  
Line Drawings ◽  
History Of ◽  
The 19Th Century ◽  
First Time

This is a comprehensive, illustrated catalogue of the 200+ marine chronometers in the collections of Royal Museums Greenwich. Every chronometer has been completely dismantled, studied and recorded, and illustrations include especially commissioned line drawings as well as photographs. The collection is also used to illustrate a newly researched and up-to-date chapter describing the history of the marine chronometer, so the book is much more than simply a catalogue. The history chapter naturally includes the story of John Harrison’s pioneering work in creating the first practical marine timekeepers, all four of which are included in the catalogue, newly photographed and described in minute detail for the first time. In fact full technical and historical data are provided for all of the marine chronometers in the collection, to an extent never before attempted, including biographical details of every maker represented. A chapter describes how the 19th century English chronometer was manufactured, and another provides comprehensive and logically arranged information on how to assess and date a given marine chronometer, something collectors and dealers find particularly difficult. For further help in identification of chronometers, appendices include a pictorial record of the number punches used by specific makers to number their movements, and the maker’s punches used by the rough movement makers. There is also a close-up pictorial guide to the various compensation balances used in chronometers in the collection, a technical Glossary of terms used in the catalogue text and a concordance of the various inventory numbers used in the collection over the years.

scholarly journals Adaptability of Ultrasonic Lamb Wave Touchscreen to the Variations in Touch Force and Touch Area

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1736
Author(s):  
Zengchong Yang ◽  
Xiucheng Liu ◽  
Bin Wu ◽  
Ren Liu
Keyword(s):  
Lamb Wave ◽  
Weight Coefficient ◽  
The Self ◽  
Reference Database ◽  
Learning Method ◽  
Improved Method ◽  
Large Area ◽  
Localization Model ◽  
Reference Databases ◽  
First Time

Previous studies on Lamb wave touchscreen (LWT) were carried out based on the assumption that the unknown touch had the consistent parameters with acoustic fingerprints in the reference database. The adaptability of LWT to the variations in touch force and touch area was investigated in this study for the first time. The automatic collection of the databases of acoustic fingerprints was realized with an experimental prototype of LWT employing three pairs of transmitter–receivers. The self-adaptive updated weight coefficient of the used transmitter–receiver pairs was employed to successfully improve the accuracy of the localization model established based on a learning method. The performance of the improved method in locating single- and two-touch actions with the reference database of different parameters was carefully evaluated. The robustness of the LWT to the variation of the touch force varied with the touch area. Moreover, it was feasible to locate touch actions of large area with reference databases of small touch areas as long as the unknown touch and the reference databases met the condition of equivalent averaged stress.

scholarly journals Efficacy of compressed sodium chloride (CSC) against E. coli and Candida auris in minutes and methods improvement for testing

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Lan N. Truong ◽  
Brayden D. Whitlock
Keyword(s):  
Sodium Chloride ◽  
Improved Method ◽  
Candida Auris ◽  
Antimicrobial Surfaces ◽  
E Coli ◽  
Route Of Transmission ◽  
The World ◽  
Short Time ◽  
First Time ◽  
Time Point

AbstractControlling infections has become one of the biggest problems in the world, whether measured in lives lost or money spent. This is worsening as pathogens continue becoming resistant to therapeutics. Antimicrobial surfaces are one strategy being investigated in an attempt to decrease the spread of infections through the most common route of transmission: surfaces, including hands. Regulators have chosen two hours as the time point at which efficacy should be measured. The objectives of this study were to characterize the new antimicrobial surface compressed sodium chloride (CSC) so that its action may be understood at timepoints more relevant to real-time infection control, under two minutes; to develop a sensitive method to test efficacy at short time points; and to investigate antifungal properties for the first time. E. coli and Candida auris are added to surfaces, and the surfaces are monitored by contact plate, or by washing into collection vats. An improved method of testing antimicrobial efficacy is reported. Antimicrobial CSC achieves at least 99.9% reduction of E. coli in the first two minutes of contact, and at least 99% reduction of C. auris in one minute.

scholarly journals Hybrid Krill Herd-ANN Model for Prediction Strength and Stiffness of Bolted Connections

Buildings ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 229
Author(s):  
Iman Faridmehr ◽  
Mehdi Nikoo ◽  
Mohammad Hajmohammadian Baghban ◽  
Raffaele Pucinotti
Keyword(s):  
Correlation Coefficient ◽  
Predictive Accuracy ◽  
Supply And Demand ◽  
Steel Structures ◽  
Ann Model ◽  
Krill Herd Algorithm ◽  
Seat Angle ◽  
Taylor Diagram ◽  
Krill Herd ◽  
Strength And Stiffness

The behavior of beam-to-column connections significantly influences the stability, strength, and stiffness of steel structures. This is particularly important in extreme non-elastic responses, i.e., earthquakes, and sudden column removal, as the fluctuation in strength and stiffness affects both supply and demand. Accordingly, it is essential to accurately estimate the strength and stiffness of connections in the analysis of and design procedures for steel structures. Beginning with the state-of-the-art, the capacity of three available component-based mechanical models to estimate the complex mechanical properties of top- and seat-angle connections with double-web angles (TSACWs), with variable parameters, were investigated. Subsequently, a novel hybrid krill herd algorithm-artificial neural network (KHA-ANN) model was proposed to acquire an informational model from the available experimental dataset. Using several statistical metrics, including the corresponding coefficient of variation (CoV), correlation coefficient (R), and the correlation coefficient provided by the Taylor diagram, this study revealed that the krill herd-ANN model achieved the most reliable predictive accuracy for the strength and stiffness of top- and seat-angle connections with double web angles.

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