Muhammad Riaz Khan

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This study presents the applicability of an ensemble of artificial neural networks (ANNs) and learning paradigms for weather forecasting in southern Saskatchewan, Canada. The proposed ensemble method for weather forecasting has advantages over other techniques like linear combination. Generally, the output of an ensemble is a weighted sum, which are(More)
This paper presents a comparative study of different neural network models for forecasting the weather of Vancouver, British Columbia, Canada. For developing the models, we used one year's data comprising of daily maximum and minimum temperature, and wind-speed. We used Multi-Layered Perceptron (MLP) and an Elman Recurrent Neural Network (ERNN), which were(More)
This paper presents a comparative study of six soft computing models namely multilayer perceptron networks, Elman recurrent neural network, radial basis function network, Hopfield model, fuzzy inference system and hybrid fuzzy neural network for the hourly electricity demand forecast of Czech Republic. The soft computing models were trained and tested using(More)
Electronic business (EB) on the Internet has been promoted as a revolutionary technology that will transform " the way we do business. " This paper presents the results of an exploratory study, which compares the financial performance (FP) of 73 publicly held U.S. corporations from the retail industry over a ten-year period. The study analyzes the financial(More)
A high density genetic map was constructed using F2 population derived from an interspecific cross of G. hirsutum × G. tomentosum. The map consisted of 3093 marker loci distributed across all the 26 chromosomes and covered 4365.3 cM of cotton genome with an average inter-marker distance of 1.48 cM. The maximum length of chromosome was 218.38 cM and the(More)
Mutations in SLC26A4 cause either syndromic or nonsyndromic hearing loss. We identified a link between hearing loss and DFNB4 in 3 of the 50 families participating in this study. Sequencing analysis revealed two SLC26A4 mutations, p.V239D and p.S57X, in affected members of the 3 families. These mutations have been previously reported in deaf individuals(More)
This paper presents a comparative study of six soft computing models namely multilayer perceptron networks, Elman recurrent neural network, radial basis function network, Hopfield model, fuzzy inference system and hybrid fuzzy neural network for the hourly electricity demand forecast of Czech Republic. The soft computing models were trained and tested using(More)
Soil salinity negatively affects growth and development as well as yield and fiber quality of cotton. The identification of quantitative trait loci (QTLs) for traits related to salt tolerance could facilitate the development of cotton cultivars with salt tolerance. The objective of this study was to map QTLs for salt tolerance in an F2:3 population derived(More)