• Chemo-inspired Genetic Algorithm for Optimizing the Piecewise Aggregate Approximation 

      Muhammad Fuad, Muhammad Marwan (Journal article; Tidsskriftartikkel; Peer reviewed, 2015)
      In a previous work we presented DEWPAA: an improved version of the piecewise aggregate approximation representation method of time series. DEWPAA uses differential evolution to set weights to different segments of the time series according to their information content. In this paper we use a hybrid of bacterial foraging and genetic algorithm (CGA) to set the weights of the different segments in our ...
    • Differential Evolution-Based Weighted Combination of Distance Metrics for k-means Clustering 

      Muhammad Fuad, Muhammad Marwan (Journal article; Tidsskriftartikkel; Peer reviewed, 2014)
    • A Haar Wavelet-based Multi-resolution Representation Method of Time Series Data 

      Muhammad Fuad, Muhammad Marwan (Peer reviewed; Journal article; Tidsskriftartikkel, 2015-01-10)
      Similarity search of time series can be efficiently handled through a multi-resolution representation scheme which offers the possibility to use pre-computed distances that are calculated and stored at indexing time and then utilized at query time together with filters in the form of exclusion conditions which speed up the search. In this paper we introduce a new multi-resolution representation ...
    • A Hybrid of Bacterial Foraging and Differential Evolution -based Distance of Sequences 

      Muhammad Fuad, Muhammad Marwan (Journal article; Tidsskriftartikkel; Peer reviewed, 2014)
    • On the Application of Bio-Inspired Optimization Algorithms to Fuzzy C-Means Clustering of Time Series 

      Muhammad Fuad, Muhammad Marwan (Journal article; Tidsskriftartikkel; Peer reviewed, 2015)
      Fuzzy c-means clustering (FCM) is a clustering method which is based on the partial membership concept. As with the other clustering methods, FCM applies a distance to cluster the data. While the Euclidean distance is widely-used to perform the clustering task, other distances have been suggested in the literature. In this paper we study the use of a weighted combination of metrics in FCM clustering ...
    • One-Step or Two-Step Optimization and the Overfitting Phenomenon:A Case Study on Time Series Classification 

      Muhammad Fuad, Muhammad Marwan (Conference object; Konferansebidrag, 2014)
      For the last few decades, optimization has been developing at a fast rate. Bio-inspired optimization algorithms are metaheuristics inspired by nature. These algorithms have been applied to solve different problems in engineering, economics, and other domains. Bio-inspired algorithms have also been applied in different branches of information technology such as networking and software engineering. ...
    • Parameter-Free Extended Edit Distance 

      Muhammad Fuad, Muhammad Marwan (Journal article; Tidsskriftartikkel; Peer reviewed, 2014)
      The edit distance is the most famous distance to compute the similarity between two strings of characters. The main drawback of the edit distance is that it is based on local procedures which reflect only a local view of similarity. To remedy this problem we presented in a previous work the extended edit distance, which adds a global view of similarity between two strings. However, the extended edit ...
    • A Pre-initialization Stage of Population-Based Bio-inspired Metaheuristics for Handling Expensive Optimization Problems 

      Muhammad Fuad, Muhammad Marwan (Journal article; Tidsskriftartikkel; Peer reviewed, 2013)
      Metaheuristics are probabilistic optimization algorithms which are applicable to a wide range of optimization problems. Bio-inspired, also called nature-inspired, optimization algorithms are the most widely-known metaheuristics. The general scheme of bio-inspired algorithms consists in an initial stage of randomly generated solutions which evolve through search operations, for several generations, ...
    • A Synergy of Artificial Bee Colony and Genetic Algorithms to Determine the Parameters of the Σ-Gram Distance 

      Muhammad Fuad, Muhammad Marwan (Journal article; Tidsskriftartikkel; Peer reviewed, 2014)
      In a previous work we presented the Σ-gram distance that computes the similarity between two sequences. This distance includes parameters that we calculated by means of an optimization process using artificial bee colony. In another work we showed how population-based bio-inspired algorithms can be sped up by applying a method that utilizes a pre-initialization stage to yield an optimal initial ...
    • A weighted minimum distance using hybridization of particle swarm optimization and Bacterial Foraging 

      Muhammad Fuad, Muhammad Marwan (Journal article; Tidsskriftartikkel; Peer reviewed, 2014)
    • When Optimization Is Just an Illusion 

      Muhammad Fuad, Muhammad Marwan (Journal article; Tidsskriftartikkel; Peer reviewed, 2013)
      Bio-inspired optimization algorithms have been successfully applied to solve many problems in engineering, science, and economics. In computer science bio-inspired optimization has different applications in different domains such as software engineering, networks, data mining, and many others. However, some applications may not be appropriate or even correct. In this paper we study this phenomenon ...