Single-solution based metaheuristic approach to a novel restricted clustering problem

2021 ◽  
Author(s):  
Jose Fernandez Goycoolea ◽  
Mario Inostroza-Ponta ◽  
Manuel Villalobos-Cid ◽  
Mauricio Marin
Keyword(s):  
Clustering Problem ◽  
Single Solution

TERRITORIAL MANAGEMENT CONTRACTS: A MODEL FOR A GLOBAL MANAGEMENT OF THE TERRITORY

2015 ◽  
Author(s):  
Lucia ROCCHI ◽  
Adriano CIANI
Keyword(s):  
Local Communities ◽  
Social Activities ◽  
Bottom Up ◽  
Global Management ◽  
Single Solution ◽  
Territorial Management ◽  
Management Contracts

Bottom-up solutions for managing the territory have been increase their importance in the last years. Local communities want to be involved in the management of the territory to avoid problems and to promote economic and social activities. Several different forms of participatory contracts have been developed during the last decades. However, a framework to enforce each single solution are required. The Territorial Management Contracts (TMCs) would like to give a contribute in such a direction. The contribute briefly illustrates the Territorial Management Contracts, to open a debate on them.

Multi-Start Jaya Algorithm for Software Module Clustering Problem

2018 ◽  
Vol 1 (1) ◽  
pp. 87-112 ◽  
Author(s):  
Kamal Z. Zamli ◽  
◽  
Abdulrahman Alsewari ◽  
Bestoun S. Ahmed ◽  
◽  
...  
Keyword(s):  
Jaya Algorithm ◽  
Software Module ◽  
Clustering Problem ◽  
Software Module Clustering

Effect of operating conditions on rejection of anionic pollutants in the water environment by nanofiltration especially in very low pressure range

1996 ◽  
Vol 34 (9) ◽  
pp. 149-156 ◽  
Author(s):  
C. Ratanatamskul ◽  
K. Yamamoto ◽  
T. Urase ◽  
S. Ohgaki
Keyword(s):  
Water Environment ◽  
Chloride Ions ◽  
Operating Conditions ◽  
Transmembrane Pressure ◽  
Operating Pressure ◽  
Nanofiltration Membranes ◽  
Single Solution ◽  
Crossflow Velocity ◽  
Membrane Type ◽  
New Generation

The recent development of new generation LPRO or nanofiltration membranes have received attraction for application in the field of wastewater and water treatment through an increasingly stringent regulation for drinking purpose and water reclamation. In this research, the application on treatment of anionic pollutants (nitrate, nitrite, phosphate, sulfate and chloride ions) have been investigated as functions of transmembrane pressure, crossflow velocity and temperature under very much lower pressure operation range (0.49 to 0.03 MPa) than any other previous research used to do. Negative rejection was also observed under very much low range of operating pressure in the case of membrane type NTR-7250. Moreover, the extended Nernst-Planck model was used for analysis of the experimental data of the rejection of nitrate, nitrite and chloride ions in single solution by considering effective charged density of the membranes.

An Improved B-hill Climbing Optimization Technique for Solving the Text Documents Clustering Problem

2020 ◽  
Vol 16 (4) ◽  
pp. 296-306 ◽  
Author(s):  
Laith Mohammad Abualigah ◽  
Essam Said Hanandeh ◽  
Ahamad Tajudin Khader ◽  
Mohammed Abdallh Otair ◽  
Shishir Kumar Shandilya
Keyword(s):  
Optimization Technique ◽  
Document Clustering ◽  
Text Clustering ◽  
Hill Climbing ◽  
Text Documents ◽  
Clustering Problem ◽  
Text Document ◽  
Text Information ◽  
Amount Of Knowledge ◽  
The Hill

Background: Considering the increasing volume of text document information on Internet pages, dealing with such a tremendous amount of knowledge becomes totally complex due to its large size. Text clustering is a common optimization problem used to manage a large amount of text information into a subset of comparable and coherent clusters. Aims: This paper presents a novel local clustering technique, namely, β-hill climbing, to solve the problem of the text document clustering through modeling the β-hill climbing technique for partitioning the similar documents into the same cluster. Methods: The β parameter is the primary innovation in β-hill climbing technique. It has been introduced in order to perform a balance between local and global search. Local search methods are successfully applied to solve the problem of the text document clustering such as; k-medoid and kmean techniques. Results: Experiments were conducted on eight benchmark standard text datasets with different characteristics taken from the Laboratory of Computational Intelligence (LABIC). The results proved that the proposed β-hill climbing achieved better results in comparison with the original hill climbing technique in solving the text clustering problem. Conclusion: The performance of the text clustering is useful by adding the β operator to the hill climbing.

Linear and Nonlinear Dynamic Behaviour

2018 ◽  
Author(s):  
Ray Huffaker ◽  
Marco Bittelli ◽  
Rodolfo Rosa
Keyword(s):  
Dynamic Behavior ◽  
Dynamic Systems ◽  
Dynamic Behaviour ◽  
Nonlinear Dynamical Systems ◽  
Logistic Map ◽  
Nonlinear Dynamical ◽  
Deterministic Dynamic ◽  
Random Behavior ◽  
Single Solution ◽  
Equivalent Systems

In this chapter, we describe how highly erratic dynamic behavior can arise from a nonlinear logistic map, and how this apparently random behavior is governed by a surprising order. With this lesson in mind, we should not be overly surprised that highly erratic and random appearing observed data might also be generated by parsimonious deterministic dynamic systems. At a minimum, we contend that researchers should apply NLTS to test for this possibility. We also introduced tools to analyze dynamic behavior that form the foundation for NLTS. In particular, we have stressed the quite unexpected capability to achieve some form of predictability even with only one trajectory at hand. In subsequent chapters, we treat known nonlinear dynamical systems as unknown, and investigate how NLTS methods rely on a single solution (or multiple solutions) generated by them to reconstruct equivalent systems. This is a conventional approach in the literature for seeing how NLTS methods work since we know what needs to be reconstructed.

scholarly journals Waste Plastic, the Challenge Facing Developing Countries—Ban It, Change It, Collect It?

Recycling ◽  
2019 ◽  
Vol 4 (1) ◽  
pp. 3 ◽  
Author(s):  
Linda Godfrey
Keyword(s):  
Developing Countries ◽  
Civil Society ◽  
Unintended Consequences ◽  
Consumption Patterns ◽  
Waste Collection ◽  
Waste Plastic ◽  
The World ◽  
Single Solution ◽  
Single Use ◽  
Taking Action

With changing consumption patterns, growing populations and increased urbanisation, developing countries face significant challenges with regards to waste management. Waste plastic is a particularly problematic one, with single-use plastic leaking into the environment, including the marine environment, at an unprecedented rate. Around the world, countries are taking action to minimise these impacts, including banning single-use plastics; changing petroleum-based plastics to alternative bio-benign products such as paper, glass or biodegradable plastics; and improving waste collection systems to ensure that all waste is appropriately collected and reprocessed or safely disposed. However, these “solutions” are often met with resistance, from business, government or civil society, due to the intended and unintended consequences, leaving many questioning the most appropriate solution to reducing the leakage. This paper argues that there is no one single solution to addressing the leakage of plastic into the environment, but that the solution is likely to be a combination of the three approaches, based on local considerations.

scholarly journals Clustering of cancer data based on Stiefel manifold for multiple views

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Jing Tian ◽  
Jianping Zhao ◽  
Chunhou Zheng
Keyword(s):  
Optimization Problem ◽  
Nearest Neighbor ◽  
Search Algorithm ◽  
Stiefel Manifold ◽  
Omics Data ◽  
K Nearest Neighbor ◽  
Cancer Data ◽  
Clustering Problem ◽  
Multiple Datasets ◽  
Cluster Class

Abstract Background In recent years, various sequencing techniques have been used to collect biomedical omics datasets. It is usually possible to obtain multiple types of omics data from a single patient sample. Clustering of omics data plays an indispensable role in biological and medical research, and it is helpful to reveal data structures from multiple collections. Nevertheless, clustering of omics data consists of many challenges. The primary challenges in omics data analysis come from high dimension of data and small size of sample. Therefore, it is difficult to find a suitable integration method for structural analysis of multiple datasets. Results In this paper, a multi-view clustering based on Stiefel manifold method (MCSM) is proposed. The MCSM method comprises three core steps. Firstly, we established a binary optimization model for the simultaneous clustering problem. Secondly, we solved the optimization problem by linear search algorithm based on Stiefel manifold. Finally, we integrated the clustering results obtained from three omics by using k-nearest neighbor method. We applied this approach to four cancer datasets on TCGA. The result shows that our method is superior to several state-of-art methods, which depends on the hypothesis that the underlying omics cluster class is the same. Conclusion Particularly, our approach has better performance than compared approaches when the underlying clusters are inconsistent. For patients with different subtypes, both consistent and differential clusters can be identified at the same time.

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