Electricity consumption forecasting using Adaptive Neuro-Fuzzy Inference System (ANFIS)

Universiti Tun Hussein Onn Malaysia (UTHM) is a developing Malaysian Technical University. There is a great development of UTHM since its formation in 1993. Therefore, it is crucial to have accurate future electricity consumption forecasting for its future energy management and saving. Even though there are previous works of electricity consumption forecasting using Adaptive Neuro-Fuzzy Inference System (ANFIS), but most of their data are multivariate data. In this study, we have only univariate data of UTHM electricity consumption from January 2009 to December 2018 and wish to forecast 2019 consumption. The univariate data was converted to multivariate and ANFIS was chosen as it carries both advantages of Artificial Neural Network (ANN) and Fuzzy Inference System (FIS). ANFIS yields the MAPE between actual and predicted electricity consumption of 0.4002% which is relatively low if compared to previous works of UTHM electricity forecasting using time series model (11.14%), and first-order fuzzy time series (5.74%), and multiple linear regression (10.62%)

Multivariate dynamic kernels for financial time series forecasting

The final publication is available at http://link.springer.com/chapter/10.1007/978-3-319-44781-0_40We propose a forecasting procedure based on multivariate dynamic kernels, with the capability of integrating information measured at different frequencies and at irregular time intervals in financial markets. A data compression process redefines the original financial time series into temporal data blocks, analyzing the temporal information of multiple time intervals. The analysis is done through multivariate dynamic kernels within support vector regression. We also propose two kernels for financial time series that are computationally efficient without a sacrifice on accuracy. The efficacy of the methodology is demonstrated by empirical experiments on forecasting the challenging S&P500 market.Peer ReviewedPostprint (author's final draft

Forecasting electricity consumption using the second-order fuzzy time series

There is a great development of Universiti Tun Hussein Onn Malaysia (UTHM) infrastructure since its formation in 1993. The development will be accompanied by the increasing demand for electricity. Hence, there is a need to forecast UTHM electricity consumption accurately so that UTHM can plan for future energy demand and utility saving decisions. Previous studies on UTHM electricity consumption prediction have been carried out using time series models, multiple linear regression and first-order fuzzy time series (FTS). The first-order FTS yield the best accuracy among these three methods. Previous forecasting problem showed higher order FTS can yield better accuracy. Therefore, in this study, the second-order FTS with trapezoidal membership function was implemented on the UTHM monthly electricity consumption from January 2009 to December 2018 to forecast January to December 2019 monthly electricity consumption. The procedure of the FTS and trapezoidal membership function was described together with January data. The second-order FTS forecast UTHM electricity consumption better than the first-order FTS

Simulation of Internal Undular Bores Propagating over a Slowly Varying Region

Internal undular bores have been observed in many parts of the world. Studies have shown that many marine structures face danger and risk of destruction caused by internal undular bores due to the amount of energy it carries. This paper looks at the transformation of internal undular bore in two-layer fluid flow under the influence of variable topography. Thus, the surface of the bottom is considered to be slowly varying. The appropriate mathematical model is the variable-coefficient extended Korteweg-de Vries equation. We are particularly interested in looking at the transformation of KdV-type and table-top undular bore over the variable topography region. The governing equation is solved numerically using the method of lines, where the spatial derivatives are first discretised using finite difference approximation so that the partial differential equation becomes a system of ordinary differential equations which is then solved by 4th order Runge-Kutta method. Our numerical results show that the evolution of internal undular bore over different types of varying depths regions leads to a number of adiabatic and non-adiabatic effects. When the depth decreases slowly, a solitary wavetrain is observed at the front of the transformed internal undular bore. On the other hand, when the depth increases slowly, we observe the generation of step-like wave and weakly nonlinear trailing wavetrain, the occurrence of multi-phase behaviour, the generation of transformed undular bore of negative polarity and diminishing transformed undular bore depending on the nature of the topography after the variable topography

Large Area Roller Embossing of Multilayered Ceramic Green Composites

In this paper, we will report our achievements in developing large area patterning of multilayered ceramic green composites using roller embossing. The aim of our research is to pattern large area ceramic green composites using a modified roller laminating apparatus, which is compatible with screen printing machines, for integration of embossing and screen printing. The instrumentation of our roller embossing apparatus, as shown in Figure1, consists of roller 1 and rollers 2. Roller 1 is heated up to the desired embossing temperature ; roller 2 is, however, kept at room temperature. The mould is a nickel template manufactured by plating nickel-based micro patterns (height : 50 $\mu$m) on a nickel film (thickness : 70 $\mu$m) ; the substrate for the roller embossing is a multilayered Heraeus Heralock HL 2000 ceramic green composite. Comparing with the conventional simultaneous embossing, the advantages of roller embossing include : (1) low embossing force ; (2) easiness of demoulding ; (3) localized area in contact with heater ; and etc. We have demonstrated the capability of large area roller embossing with a panel size of 150mmx 150mm on the mentioned substrate. We have explored and confirmed the impact of parameters (feed speed, temperature of roller and applied pressure) to the pattern quality of roller embossing. Furthermore, under the optimized process parameters, we characterized the variations of pattern dimension over the panel area, and calculated a scaling factor in order to make the panel compatible with other processes. Figure 2 shows the embossed patterns on a 150mmx 150mm green ceramic panel.Comment: Submitted on behalf of EDA Publishing Association (http://irevues.inist.fr/handle/2042/16838

Preoperative Kidney Function linked to mortality and readmission outcomes at Day 90 and 30 in Older Emergency Surgical Patients

Grants were received from British Geriatric Society and The Renal Association to support Louis EvansPeer reviewedPublisher PD

Mechanical And Thermal Properties Of Hydroxyapatite Filled Poly(Methyl Methacrylate) Composites.

Poly(methyl methacrylate) (PMMA) filled with hydroxyapatite (HA) filler has been widely used in biomaterial application. Acrylic denture base material was prepared from PMMA filled with HA

Insecticidal Effects of Organotin(IV) Compounds on Plutella Xylostella (L.) Larvae. II. Inhibitory Potencies Against Acetylcholinesterase and Evidence for Synergism in Tests With Bacillus Thuringiensis(BER.) and Malathion

Features of pesticide synergism and acetylcholinesterase (AChE) inhibition (in vitro) were studied using a selected range of organotin compounds against the early 4th instar larvae of a highly resistant strain of the diamondback moth (DBM), Plutella xylostella, a major universal pest of cruciferous vegetables