scholarly journals Stochastic Metaheuristics as Sampling Techniques using Swarm Intelligence

10.5772/5105 ◽  
2007 ◽  
Author(s):  
Johann Dreo ◽  
Patrick Siarry
Keyword(s):  
Swarm Intelligence ◽  
Sampling Techniques

So you are looking for spit! An investigation of parents' perspectives of saliva sampling techniques

2010 ◽  
Author(s):  
Christine O'Farrelly ◽  
Eilis Hennessy
Keyword(s):  
Sampling Techniques

Handling Imbalanced Data for Real-Time Crash Prediction: Application of Boosting and Sampling Techniques

2021 ◽  
Vol 147 (3) ◽  
pp. 04020165
Author(s):  
Amin Ariannezhad ◽  
Abolfazl Karimpour ◽  
Xiao Qin ◽  
Yao-Jan Wu ◽  
Yasamin Salmani
Keyword(s):  
Real Time ◽  
Imbalanced Data ◽  
Sampling Techniques ◽  
Crash Prediction

271. A Comparison of Oil Mist Sampling Techniques Using Various Oils and Oil Concentrations

1999 ◽  
Author(s):  
J. Voelker ◽  
P. Reist
Keyword(s):  
Sampling Techniques ◽  
Oil Mist

Penerapan Psikologi Islam dalam Praktek Profesi Psikolog Muslim

2020 ◽  
Vol 3 (1) ◽  
pp. 47-60
Author(s):  
Yulia Hairina ◽  
Mubarak Mubarak
Keyword(s):  
Discussion Group ◽  
Qualitative Approach ◽  
Psychological Services ◽  
Reference Source ◽  
Sampling Techniques ◽  
Purposive Sampling ◽  
Primary Reference ◽  
Islamic Psychology

This research aims to describe the application of Islamic Psychology in the practice of Muslim psychologists and the obstacles in its application. This study uses a qualitative approach for taking respondents using purposive sampling techniques. There are twenty respondents in this study. The method used in collecting data from this study is the interview and Focus Discussion Group. This study found that the understanding of Islamic Psychology was quite diverse, but in essence, an approach that used the Qur'an and Hadist was the primary reference source. Its application, including the psychological services, and the process of counseling and therapy were carried out by integrating psychology and Islam. The cases also handled varied, not limited to severe or mild cases. The challenges were related to the ability of the psychologists and the acceptance of the clients.

Performance Analysis of TBC-ACO Routing Protocol with Existing Routing Protocols of Wireless Sensor Networks

2017 ◽  
Vol 7 (8) ◽  
pp. 169
Author(s):  
A. Radhika ◽  
D. Haritha
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Swarm Intelligence ◽  
Routing Protocol ◽  
Routing Protocols ◽  
Energy Efficient ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Congestion Aware

Wireless Sensor Networks, have witnessed significant amount of improvement in research across various areas like Routing, Security, Localization, Deployment and above all Energy Efficiency. Congestion is a problem of  importance in resource constrained Wireless Sensor Networks, especially for large networks, where the traffic loads exceed the available capacity of the resources . Sensor nodes are prone to failure and the misbehaviour of these faulty nodes creates further congestion. The resulting effect is a degradation in network performance, additional computation and increased energy consumption, which in turn decreases network lifetime. Hence, the data packet routing algorithm should consider congestion as one of the parameters, in addition to the role of the faulty nodes and not merely energy efficient protocols .Nowadays, the main central point of attraction is the concept of Swarm Intelligence based techniques integration in WSN.  Swarm Intelligence based Computational Swarm Intelligence Techniques have improvised WSN in terms of efficiency, Performance, robustness and scalability. The main objective of this research paper is to propose congestion aware , energy efficient, routing approach that utilizes Ant Colony Optimization, in which faulty nodes are isolated by means of the concept of trust further we compare the performance of various existing routing protocols like AODV, DSDV and DSR routing protocols, ACO Based Routing Protocol  with Trust Based Congestion aware ACO Based Routing in terms of End to End Delay, Packet Delivery Rate, Routing Overhead, Throughput and Energy Efficiency. Simulation based results and data analysis shows that overall TBC-ACO is 150% more efficient in terms of overall performance as compared to other existing routing protocols for Wireless Sensor Networks.

An Improved Ad-Hoc Routing Protocol for MANETs using Swarm Intelligence Technique

2015 ◽  
Vol 2 (3) ◽  
pp. 21-29
Author(s):  
P. Sarika ◽  
◽  
Rama Prasad V. Vaddella ◽  
Keyword(s):  
Swarm Intelligence ◽  
Routing Protocol ◽  
Ad Hoc ◽  
Ad Hoc Routing ◽  
Ad Hoc Routing Protocol ◽  
Intelligence Technique
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