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All Journal International Journal of Electrical and Computer Engineering Aceh Journal of Animal Science
Isaac, Samuel
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Agriculture, Biological Sciences & Forestry Computer Science & IT Earth & Planetary Sciences Electrical & Electronics Engineering Environmental Science Immunology & microbiology Physics Veterinary

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Voltage collapse prediction using artificial neural network Isaac, Samuel; Adebola, Soyemi; Ayokunle, Awelewa; James, Katende; Claudius, Awosope
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 1: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i1.pp124-132

Abstract

Unalleviated voltage instability frequently results in voltage collapse; which is a cause of concern in power system networks across the globe but particularly in developing countries. This study proposed an online voltage collapse prediction model through the application of a machine learning technique and a voltage stability index called the new line stability index (NLSI_1). The approach proposed is based on a multilayer feed-forward neural network whose inputs are the variables of the NLSI_1. The efficacy of the method was validated using the testing on the IEEE 14-bus system and the Nigeria 330-kV, 28-bus National Grid (NNG). The results of the simulations indicate that the proposed approach accurately predicted the voltage stability index with an R-value of 0.9975 with a mean square error (MSE) of 2.182415x10−5 for the IEEE 14-bus system and an R-value of 0.9989 with an MSE of 1.2527x10−7 for the NNG 28 bus system. The results presented in this paper agree with those found in the literature.
Effect of diets containing raw and processed pigeon pea seed meal supplemented with enzyme on external and internal egg quality characteristics of laying quails Coturnix coturnix japonica Akintunde, Afolabi Rotimi; Oguntoye, Mutiu Ayogbe; Adeoye, Samson O. B.; Olusiyi, Japhet Adeniyi; Isaac, Samuel; Istifanus, Emmanuel Filian
Aceh Journal of Animal Science Vol 9, No 1 (2024): February 2024
Publisher : Syiah Kuala University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13170/ajas.9.1.29805

Abstract

Three hundred and sixty, six-week old Japanese quail (Coturnix coturnix japonica) hens were used to evaluate the effect of processed pigeon pea seed meal (PPSM) supplemented with enzyme (Vegpro) on egg quality characteristics of laying birds. The processing methods were soaking (24, 48 and 72 hours), fermentation (72 hours), boiling (60 minutes) and roasting (30 minutes). The birds were divided into eight groups of 45 per treatment each replicated three times with 15 birds per replicate in a completely randomized design. Eight experimental diets were formulated containing processed PPSM at 30 % of diet representing T1 (control), T2 (raw PPSM), T3 (soaked PPSM for 24 hours), T4 (soaked PPSM for 48 hours), T5 (soaked PPSM for 72 hours), T6 (soaked PPSM for 24 hours and fermented for 72 hours), T7 (boiling for 60 minutes) and T8 (roasted PPSM for 30 minutes) respectively. The experiment lasted for 20 weeks. Feed and water were provided ad libitum. The results showed that enzyme supplementation of diets containing raw and processed PPSM had no significant (p0.05) effect on egg weight, egg height, egg diameter, egg shape index, egg shell thickness as well as albumen height, albumen diameter, albumen weight, yolk diameter, yolk weight, yolk index and haugh unit across the dietary treatments as these parameters were statistically similar. It was concluded that enzyme supplementation of raw and processed PPSM based diets had no significant effect on the egg quality characteristics of laying quail.
Co-Authors Adebola, Soyemi Adeoye, Samson O. B. Akintunde, Afolabi Rotimi Ayokunle, Awelewa Claudius, Awosope Istifanus, Emmanuel Filian James, Katende Oguntoye, Mutiu Ayogbe Olusiyi, Japhet Adeniyi