Example of International Journal of Advanced Intelligence Paradigms format
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Example of International Journal of Advanced Intelligence Paradigms format Example of International Journal of Advanced Intelligence Paradigms format Example of International Journal of Advanced Intelligence Paradigms format Example of International Journal of Advanced Intelligence Paradigms format Example of International Journal of Advanced Intelligence Paradigms format Example of International Journal of Advanced Intelligence Paradigms format Example of International Journal of Advanced Intelligence Paradigms format Example of International Journal of Advanced Intelligence Paradigms format Example of International Journal of Advanced Intelligence Paradigms format Example of International Journal of Advanced Intelligence Paradigms format Example of International Journal of Advanced Intelligence Paradigms format Example of International Journal of Advanced Intelligence Paradigms format Example of International Journal of Advanced Intelligence Paradigms format Example of International Journal of Advanced Intelligence Paradigms format Example of International Journal of Advanced Intelligence Paradigms format
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Example of International Journal of Advanced Intelligence Paradigms format Example of International Journal of Advanced Intelligence Paradigms format Example of International Journal of Advanced Intelligence Paradigms format Example of International Journal of Advanced Intelligence Paradigms format Example of International Journal of Advanced Intelligence Paradigms format Example of International Journal of Advanced Intelligence Paradigms format Example of International Journal of Advanced Intelligence Paradigms format Example of International Journal of Advanced Intelligence Paradigms format Example of International Journal of Advanced Intelligence Paradigms format Example of International Journal of Advanced Intelligence Paradigms format Example of International Journal of Advanced Intelligence Paradigms format Example of International Journal of Advanced Intelligence Paradigms format Example of International Journal of Advanced Intelligence Paradigms format Example of International Journal of Advanced Intelligence Paradigms format Example of International Journal of Advanced Intelligence Paradigms format
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open access Open Access

International Journal of Advanced Intelligence Paradigms — Template for authors

Categories Rank Trend in last 3 yrs
Engineering (all) #195 of 297 down down by 44 ranks
Applied Mathematics #407 of 548 down down by 66 ranks
Computer Science (all) #169 of 226 down down by 20 ranks
journal-quality-icon Journal quality:
Medium
calendar-icon Last 4 years overview: 238 Published Papers | 227 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 15/07/2020
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Related Journals

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Quality:  
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CiteRatio: 4.3
SJR: 1.624
SNIP: 1.688
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Journal Performance & Insights

CiteRatio

SCImago Journal Rank (SJR)

Source Normalized Impact per Paper (SNIP)

A measure of average citations received per peer-reviewed paper published in the journal.

Measures weighted citations received by the journal. Citation weighting depends on the categories and prestige of the citing journal.

Measures actual citations received relative to citations expected for the journal's category.

1.0

25% from 2019

CiteRatio for International Journal of Advanced Intelligence Paradigms from 2016 - 2020
Year Value
2020 1.0
2019 0.8
2018 0.8
2017 0.8
2016 0.8
graph view Graph view
table view Table view

0.158

7% from 2019

SJR for International Journal of Advanced Intelligence Paradigms from 2016 - 2020
Year Value
2020 0.158
2019 0.147
2018 0.146
2017 0.144
2016 0.184
graph view Graph view
table view Table view

0.36

20% from 2019

SNIP for International Journal of Advanced Intelligence Paradigms from 2016 - 2020
Year Value
2020 0.36
2019 0.299
2018 0.51
2017 0.793
2016 0.645
graph view Graph view
table view Table view

insights Insights

  • CiteRatio of this journal has increased by 25% in last years.
  • This journal’s CiteRatio is in the top 10 percentile category.

insights Insights

  • SJR of this journal has increased by 7% in last years.
  • This journal’s SJR is in the top 10 percentile category.

insights Insights

  • SNIP of this journal has increased by 20% in last years.
  • This journal’s SNIP is in the top 10 percentile category.

International Journal of Advanced Intelligence Paradigms

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Inderscience Publishers

International Journal of Advanced Intelligence Paradigms

IJAIP fosters the exchange and dissemination of applications and case studies in the area of advanced intelligence paradigms among education and research professionals. The thrust of the journal is to publish papers dealing with the design, development, testing, implementation...... Read More

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Last updated on
14 Jul 2020
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ISSN
1755-0386
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Acceptance Rate
Not provided
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Frequency
Not provided
i
Open Access
No
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Sherpa RoMEO Archiving Policy
Yellow faq
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Plagiarism Check
Available via Turnitin
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Endnote Style
Download Available
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Bibliography Name
plainnat
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Citation Type
Author Year
(Blonder et al., 1982)
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Bibliography Example
Beenakker, C. W. J. (2006). ‘Specular Andreev Reflection in Graphene’. Phys. Rev. Lett., Vol 97, No 6, pp. 067007.

Top papers written in this journal

Journal Article DOI: 10.1504/IJAIP.2013.054681
Artificial bee colony algorithm: a survey
Jagdish Chand Bansal1, Harish Sharma2, Shimpi Singh Jadon2

Abstract:

In recent years, swarm intelligence has proven its importance for the solution of those problems that cannot be easily dealt with classical mathematical techniques The foraging behaviour of honey bees produces an intelligent social behaviour and falls in the category of swarm intelligence Artificial bee colony ABC algorithm i... In recent years, swarm intelligence has proven its importance for the solution of those problems that cannot be easily dealt with classical mathematical techniques The foraging behaviour of honey bees produces an intelligent social behaviour and falls in the category of swarm intelligence Artificial bee colony ABC algorithm is a simulation of honey bee foraging behaviour, established by Karaboga in 2005 Since its inception, a lot of research has been carried out to make ABC more efficient and to apply it on different types of problems This paper presents a review on ABC developments, applications, comparative performance and future research perspectives read more read less

Topics:

Artificial bee colony algorithm (79%)79% related to the paper, Honey bee (62%)62% related to the paper, Swarm intelligence (57%)57% related to the paper, Metaheuristic (53%)53% related to the paper
144 Citations
Journal Article DOI: 10.1504/IJAIP.2018.10010530
Health data analytics using scalable logistic regression with stochastic gradient descent
Gunasekaran Manogaran1, Daphne Lopez1

Abstract:

As wearable medical sensors continuously generate enormous data, it is difficult to process and analyse. This paper focuses on developing scalable sensor data processing architecture in cloud computing to store and process body sensor data for healthcare applications. Proposed architecture uses big data technologies such as A... As wearable medical sensors continuously generate enormous data, it is difficult to process and analyse. This paper focuses on developing scalable sensor data processing architecture in cloud computing to store and process body sensor data for healthcare applications. Proposed architecture uses big data technologies such as Apache Flume, Apache Pig and Apache HBase to collect and store huge sensor data in the Amazon web service. Apache Mahout implementation of MapReduce-based online stochastic gradient descent algorithm is used in the logistic regression to develop the scalable diagnosis model. Cleveland heart disease database (CHDD) is used to train the logistic regression model. Wearable body sensors are used to get the blood pressure, blood sugar level and heart rate of the patient to predict the heart disease status. Proposed prediction model efficiently classifies the heart disease with the accuracy of training and validation sample is 81.99% and 81.52%, respectively. read more read less

Topics:

Stochastic gradient descent (53%)53% related to the paper
92 Citations
Journal Article DOI: 10.1504/IJAIP.2019.096957
A survey on internet of vehicles: applications, technologies, challenges and opportunities
M. K. Priyan1, G. Usha Devi1

Abstract:

This work aims to provide a survey on internet of things (IoT), internet of vehicles (IoV) and internet of everything (IoE). The internet of things (IoT) provides interconnection between various physical devices such as sensors devices, mobile phones, laptop, PDA and so on. Nowadays, IoT also enables connection between vehicl... This work aims to provide a survey on internet of things (IoT), internet of vehicles (IoV) and internet of everything (IoE). The internet of things (IoT) provides interconnection between various physical devices such as sensors devices, mobile phones, laptop, PDA and so on. Nowadays, IoT also enables connection between vehicles, buildings and other items that are fixed with sensors, actuators and gateways. Internet of vehicles (IoV) is identified from the internet of things (IoT). Internet of vehicles (IoV) is used to make an interconnection between the things, vehicles and environments to transfer the data and information between the networks. Internet of everything is an enhanced version of internet-based technologies such as internet of things, internet of humans and internet of digital. IoE provides end to end connectivity among procedures, knowledge and ideas engaged across all connectivity use cases. This paper discusses various challenges and issues in modern IoT, IoV, and IoE system. In addition, this paper also discusses security issues and various application of IoT in healthcare. Though IoT devices are used in modern applications with good performance, however, some challenges still exist. In order to overcome these issues, various open research problems are identified in this paper. read more read less

Topics:

The Internet (65%)65% related to the paper
46 Citations
Journal Article DOI: 10.1504/IJAIP.2017.10009223
Particle swarm optimisation-based parameters optimisation of PID controller for load frequency control of multi-area reheat thermal power systems

Abstract:

The current study presents the load frequency control (LFC) of multi-area reheat thermal power system with proportional-integral-derivative (PID) controller. The interconnected control areas are provided with a single stage reheat turbine in all areas. The proportional gain (KP), integral gain (KI) and derivative gain (KD) va... The current study presents the load frequency control (LFC) of multi-area reheat thermal power system with proportional-integral-derivative (PID) controller. The interconnected control areas are provided with a single stage reheat turbine in all areas. The proportional gain (KP), integral gain (KI) and derivative gain (KD) values of the PID controller are simultaneously optimised using recent and powerful evolutionary computational intelligence technique, namely the particle swarm optimisation (PSO) algorithm. The superiority of the PSO-based PID controller has been proved by comparing its performance to recent modern optimisation techniques such as hill climbing (HC) algorithm and genetic algorithm (GA) tuned controllers for the same multi-area thermal power system. For the analysis, the time domain specification and 1% step load perturbation (1% SLP) are considered in thermal area 1. The simulation result showed that the proposed PSO-based PID controller provides superior dynamic response over other optimisation technique (HC and GA)-based PID controller. read more read less

Topics:

PID controller (63%)63% related to the paper, Particle swarm optimization (52%)52% related to the paper, Proportional control (50%)50% related to the paper
44 Citations
Journal Article DOI: 10.1504/IJAIP.2018.10010164
The recommender system: a survey
Bushra Alhijawi1, Yousef Kilani1

Abstract:

Recommender system is a helpful tool for helping the user in cutting the time needs to find personalised products, documents, friends, places and services. In addition, the recommender system handles the century web problem: information overload. In the same time, many environments or technologies (i.e., cloud, mobile, social... Recommender system is a helpful tool for helping the user in cutting the time needs to find personalised products, documents, friends, places and services. In addition, the recommender system handles the century web problem: information overload. In the same time, many environments or technologies (i.e., cloud, mobile, social network) become popular today and facing the problem of large amount of information. Therefore, the researchers recognise that the recommender system is a suitable solution to this problem in those environments. This paper, reviews the recent research papers that were applied the recommender system in mobile, social network, or cloud environment. We classify these recommender systems into four groups (i.e., mobile recommender system, social recommender system, cloud recommender system and traditional (PC) recommender system) depending on technology or environment that the RS is applied in. This survey presents some compression, advantages and challenges of these types of recommender systems. Also, it will directly support researchers and professionals in their understanding of those types of recommender systems. read more read less

Topics:

Recommender system (66%)66% related to the paper, Cold start (61%)61% related to the paper, Collaborative filtering (60%)60% related to the paper, Cloud computing (51%)51% related to the paper
42 Citations
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13. What is Sherpa RoMEO Archiving Policy for International Journal of Advanced Intelligence Paradigms?

SHERPA/RoMEO Database

We extracted this data from Sherpa Romeo to help researchers understand the access level of this journal in accordance with the Sherpa Romeo Archiving Policy for International Journal of Advanced Intelligence Paradigms. The table below indicates the level of access a journal has as per Sherpa Romeo's archiving policy.

RoMEO Colour Archiving policy
Green Can archive pre-print and post-print or publisher's version/PDF
Blue Can archive post-print (ie final draft post-refereeing) or publisher's version/PDF
Yellow Can archive pre-print (ie pre-refereeing)
White Archiving not formally supported
FYI:
  1. Pre-prints as being the version of the paper before peer review and
  2. Post-prints as being the version of the paper after peer-review, with revisions having been made.

14. What are the most common citation types In International Journal of Advanced Intelligence Paradigms?

The 5 most common citation types in order of usage for International Journal of Advanced Intelligence Paradigms are:.

S. No. Citation Style Type
1. Author Year
2. Numbered
3. Numbered (Superscripted)
4. Author Year (Cited Pages)
5. Footnote

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Yes, SciSpace provides this functionality. After signing up, you would need to import your existing references from Word or Bib file to SciSpace. Then SciSpace would allow you to download your references in International Journal of Advanced Intelligence Paradigms Endnote style according to Elsevier guidelines.

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