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    <title>DSpace Collection:</title>
    <link>http://dspace2020.uniten.edu.my:8080/handle/123456789/19216</link>
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    <pubDate>Mon, 13 Jul 2026 12:19:39 GMT</pubDate>
    <dc:date>2026-07-13T12:19:39Z</dc:date>
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      <title>Predicting freshwater production in seawater greenhouses using hybrid artificial neural network models</title>
      <link>http://dspace2020.uniten.edu.my:8080/handle/123456789/21674</link>
      <description>Title: Predicting freshwater production in seawater greenhouses using hybrid artificial neural network models
Authors: Panahi F.; Ahmed A.N.; Singh V.P.; Ehtearm M.; elshafie A.; Torabi Haghighi A.
Abstract: Freshwater production in seawater greenhouses (SWGH) is an important topic for decision-makers in arid lands. Since arid and semi-arid lands face water shortages, the use of SWGH helps farmers to supply water. This study proposed an integrated artificial neural network (ANN) model, namely, the ANN-antlion optimization algorithm (ANN-ALO), for predicting freshwater production in a seawater greenhouse. The width, length, and height of the evaporators and the roof transparency coefficient of the SWGH were used as the inputs of the models. The ability of ANN-ALO was benchmarked against the ANN-particle swarm optimization (ANN-PSO), ANN, and ANN-bat algorithms (ANN-BA). The novelties of the current study are the novel hybrid ANN models, the fuzzy reasoning concept for reducing the computational time, the comprehensive analysis of the uncertainty of the parameters and inputs, and the use of non-climate data. Comparing the models’ performances in the test phase demonstrated that the ANN-ALO model performed best, with a Root Mean Square Error (RMSE) value that was 18%, 33%, and 39% lower than that of the ANN-BA, ANN-PSO, and ANN models, respectively. For the ANN model, the percent bias (PBIAS) value in the training stage was 0.20, whereas for the ANN-BA, ANN-PSO, and ANN-ALO models, it was 0.14, 0.16, and 0.12, respectively. This study also indicated that the width of the seawater greenhouse was the most important parameter for predicting freshwater production. Furthermore, the results suggested that an evaporator height of 2 m resulted in the highest predicted freshwater production for all the widths except 200 m. The lowest freshwater production for different widths occurred at an evaporator height of 3 m. The generalized likelihood estimation for uncertainty analysis indicated that the uncertainty of the input parameters was lower than that of the model parameters. © 2021 Elsevier Ltd</description>
      <pubDate>Fri, 01 Jan 2021 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">http://dspace2020.uniten.edu.my:8080/handle/123456789/21674</guid>
      <dc:date>2021-01-01T00:00:00Z</dc:date>
    </item>
    <item>
      <title>Initial electric field changes of lightning flashes in tropical thunderstorms and their relationship to the lightning initiation mechanism</title>
      <link>http://dspace2020.uniten.edu.my:8080/handle/123456789/21327</link>
      <description>Title: Initial electric field changes of lightning flashes in tropical thunderstorms and their relationship to the lightning initiation mechanism
Authors: Sabri M.H.M..; Ahmad M.R.; Esa M.R.M.; Periannan D.; Lu G.; Zhang H.; Cooray V.; Williams E.; Aziz M.Z.A.A.; Abdul-Malek Z.; Alkahtani A.A.; Kadir M.Z.A.A.B
Abstract: In this paper, the key finding is that all the examined first classic Initial Breakdown (IB) pulses in tropical flashes within the reversal distance were found to be initiated by a clearly detectable Initial E-field Change or IEC (45 –CG, 32 normal IC, and 3 IC initiated by +NBE). The durations of IECs for both –CG and IC flashes in tropical storms were longer than in Florida storms. On the other hand, for the magnitudes of the E-change, the values were smaller compared to Florida storms with averages of 0.30 V/m compared to 1.65 V/m for –CG flashes, and −0.81 V/m compared to −6.30 V/m for IC flashes. The IEC process of lightning flashes in tropical regions took longer to increase the local electric field in order to produce the first IB pulse because of the smaller magnitude of E-change. On the other hand, in Florida storms, the IEC process took a shorter time to increase the local electric field to produce the first IB pulse because of the larger magnitude of E-change. We found that very high frequency (VHF) pulses for tropical thunderstorms started sometime prior to the onset of the IECs. They started between 12.69 and 251.60 μs before the initiation of the IEC for two normal IC flashes. The first two VHF pulses were detected alone without narrow IB pulses (fast antenna and slow antenna records) or any pulses from the B-field and dE/dt records. Furthermore, the VHF pulses for three IC flashes initiated by +NBEs were also detected before the onset of the IEC. The IEC started immediately after the detection of the +NBE. It is clear that the IEC is initiated by VHF pulses. It can be suggested that lightning is initiated by Fast Positive Breakdowns or FPBs (which emit strong VHF pulses and large +NBEs) and is followed by several negative breakdowns (weak VHF pulses and/or weak NBE-type pulses) before the IEC started. For the case of normal IC flashes, several weaker VHF pulses (mean values of 41.97 mV and 46.4 mV compared to the amplitudes of the VHF pulses of +NBEs of around 800 mV) were detected before the onset of the IEC. As FPBs can occur with a wide range of VHF strengths and E-change amplitudes, it can be suggested these weak VHF pulses accompanied by narrow IB pulses or weak NBE-type pulses detected before the onset of IEC are actually FPBs followed by negative breakdowns or several attempted FPBs. © 2019 Elsevier B.V.</description>
      <pubDate>Tue, 01 Jan 2019 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">http://dspace2020.uniten.edu.my:8080/handle/123456789/21327</guid>
      <dc:date>2019-01-01T00:00:00Z</dc:date>
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