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- articleMay 2017
Efficient Particle Swarm Optimized Particle Filter Based Improved Multiple Model Tracking Algorithm
Computational Intelligence (COMI), Volume 33, Issue 2May 2017, Pages 262–279https://doi.org/10.1111/coin.12084To meet the requirements of modern radar maneuvering target tracking system and remedy the defects of interacting multiple model based on particle filter, noninteracting multiple model NIMM and enhanced particle swarm optimized particle filter EPSO-PF ...
- articleMay 2017
Evolutionary Clustering for Mining and Tracking Dynamic Multilayer Networks
Computational Intelligence (COMI), Volume 33, Issue 2May 2017, Pages 181–209https://doi.org/10.1111/coin.12074This article proposes a framework for community discovery in temporal multiplex networks by extending the evolutionary clustering approach to encompass both time and multiple dimensions. In this extended framework, the problem of finding community ...
- articleFebruary 2017
Multiobjective Optimization Techniques for Selecting Important Metrics in the Design of Ensemble Systems
Computational Intelligence (COMI), Volume 33, Issue 1February 2017, Pages 119–143https://doi.org/10.1111/coin.12090Ensemble systems are classification structures that apply a two-level decision-making process, in which the first level produces the outputs of the individual classifiers and the second level produces the output of the combination method final output. ...
- articleFebruary 2017
Evolutionary Algorithm-Based Radial Basis Function Neural Network Training for Industrial Personal Computer Sales Forecasting
Computational Intelligence (COMI), Volume 33, Issue 1February 2017, Pages 56–76https://doi.org/10.1111/coin.12073Forecasting is one of the crucial factors in applications because it ensures the effective allocation of capacity and proper amount of inventory. Because Box-Jenkins models using linear forecasting have their constraint to predict complexity in the real ...
- articleFebruary 2017
Computational Technique for an Efficient Classification of Protein Sequences With Distance-Based Sequence Encoding Algorithm
Computational Intelligence (COMI), Volume 33, Issue 1February 2017, Pages 32–55https://doi.org/10.1111/coin.12069Machine learning is being implemented in bioinformatics and computational biology to solve challenging problems emerged in the analysis and modeling of biological data such as DNA, RNA, and protein. The major problems in classifying protein sequences ...
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- articleNovember 2016
A Fast and Accurate Feature Selection Algorithm Based on Binary Consistency Measure
Computational Intelligence (COMI), Volume 32, Issue 4November 2016, Pages 646–667https://doi.org/10.1111/coin.12072Consistency-based feature selection is an important category of feature selection research, and its advantage over other categories is due to consistency measures used to include the effect of interaction among features into evaluation of relevance of ...
- articleNovember 2016
A Multicriteria Weighted Vote-Based Classifier Ensemble for Heart Disease Prediction
Computational Intelligence (COMI), Volume 32, Issue 4November 2016, Pages 615–645https://doi.org/10.1111/coin.12070The availability of a large amount of medical data leads to the need of intelligent disease prediction and analysis tools to extract hidden information. A large number of data mining and statistical analysis tools are used for disease prediction. Single ...
- articleNovember 2016
A Multiagent Evolutionary Method for Detecting Communities in Complex Networks
Computational Intelligence (COMI), Volume 32, Issue 4November 2016, Pages 587–614https://doi.org/10.1111/coin.12067Community structure detection in complex networks contributes greatly to the understanding of complex mechanisms in many fields. In this article, we propose a multiagent evolutionary method for discovering communities in a complex network. The focus of ...
- articleAugust 2016
Document Clustering With Dual Supervision Through Feature Reweighting
Computational Intelligence (COMI), Volume 32, Issue 3August 2016, Pages 480–513https://doi.org/10.1111/coin.12064Traditional semi-supervised clustering uses only limited user supervision in the form of instance seeds for clusters and pairwise instance constraints to aid unsupervised clustering. However, user supervision can also be provided in alternative forms ...
- articleAugust 2016
A Generic Ensemble Approach to Estimate Multidimensional Likelihood in Bayesian Classifier Learning
Computational Intelligence (COMI), Volume 32, Issue 3August 2016, Pages 458–479https://doi.org/10.1111/coin.12063In Bayesian classifier learning, estimating the joint probability distribution px,y or the likelihood px|y directly from training data is considered to be difficult, especially in large multidimensional data sets. To circumvent this difficulty, existing ...
- articleAugust 2016
An Algorithm for Clustering Using L1-Norm Based on Hyperbolic Smoothing Technique
Computational Intelligence (COMI), Volume 32, Issue 3August 2016, Pages 439–457https://doi.org/10.1111/coin.12062Cluster analysis deals with the problem of organization of a collection of objects into clusters based on a similarity measure, which can be defined using various distance functions. The use of different similarity measures allows one to find different ...
- articleAugust 2016
A Rolling Grey Model Optimized by Particle Swarm Optimization in Economic Prediction
Computational Intelligence (COMI), Volume 32, Issue 3August 2016, Pages 391–419https://doi.org/10.1111/coin.12059Grey system theory has been widely used to forecast the economic data that are often nonlinear, irregular, and nonstationary. Current forecasting models based on grey system theory could adapt to various economic time series data. However, these models ...
- articleMay 2016
Creating Decision Trees from Rules using RBDT-1
Computational Intelligence (COMI), Volume 32, Issue 2May 2016, Pages 216–239https://doi.org/10.1111/coin.12049Most of the methods that generate decision trees for a specific problem use the examples of data instances in the decision tree-generation process. This article proposes a method called RBDT-1-rule-based decision tree-for learning a decision tree from a ...
- articleMay 2016
Missing Value Imputation with Unsupervised Backpropagation
Computational Intelligence (COMI), Volume 32, Issue 2May 2016, Pages 196–215https://doi.org/10.1111/coin.12048Many data mining and data analysis techniques operate on dense matrices or complete tables of data. Real-world data sets, however, often contain unknown values. Even many classification algorithms that are designed to operate with missing values still ...
- articleMay 2016
A Comparative Evaluation of Curriculum Learning with Filtering and Boosting in Supervised Classification Problems
Computational Intelligence (COMI), Volume 32, Issue 2May 2016, Pages 167–195https://doi.org/10.1111/coin.12047Not all instances in a data set are equally beneficial for inferring a model of the data, and some instances such as outliers can be detrimental. Several machine learning techniques treat the instances in a data set differently during training such as ...
- articleNovember 2015
Building a Language-Independent Discourse Parser using Universal Networking Language
Computational Intelligence (COMI), Volume 31, Issue 4November 2015, Pages 593–618https://doi.org/10.1111/coin.12037Discourse parsing has become an inevitable task to process information in the natural language processing arena. Parsing complex discourse structures beyond the sentence level is a significant challenge. This article proposes a discourse parser that ...
- articleAugust 2015
Training Multiagent Systems by Q-Learning: Approaches and Empirical Results
Computational Intelligence (COMI), Volume 31, Issue 3August 2015, Pages 498–512https://doi.org/10.1111/coin.12035Multiagent systems are increasingly present in computational environments. However, the problem of agent design or control is an open research field. Reinforcement learning approaches offer solutions that allow autonomous learning with minimal ...
- articleAugust 2015
Automated Testing of Physical Security: Red Teaming Through Machine Learning
Computational Intelligence (COMI), Volume 31, Issue 3August 2015, Pages 465–497https://doi.org/10.1111/coin.12034Modern surveillance systems for practical applications with diverse and mobile sensors are large, complex, and expensive. It is known that unexpected behaviors can emerge from such systems, and when these behaviors correspond to weaknesses in a ...
- articleAugust 2015
An Infrastructure for Argumentative Agents
Computational Intelligence (COMI), Volume 31, Issue 3August 2015, Pages 418–441https://doi.org/10.1111/coin.12030Multiagent systems are suitable for providing a framework that allows agents to perform collaborative processes in a social context. Furthermore, argumentation is a natural way of reaching agreements between several parties. However, it is difficult to ...
- articleMay 2015
Undirected Dependency Parsing
Computational Intelligence (COMI), Volume 31, Issue 2May 2015, Pages 348–384https://doi.org/10.1111/coin.12027Dependency parsers, which are widely used in natural language processing tasks, employ a representation of syntax in which the structure of sentences is expressed in the form of directed links dependencies between their words. In this article, we ...