Wind generation forecasting methods and proliferation of artificial neural network:A review of five years research trend

To sustain a clean environment by reducing fossil fuels-based energies and increasing the integration of renewable-based energy sources, i.e., wind and solar power, have become the national policy for many countries. The increasing demand for renewable energy sources, such as wind, has created interest in the economic and technical issues related to the integration into the power grids. Having an intermittent nature and wind generation forecasting is a crucial aspect of ensuring the optimum grid control and design in power plants. Accurate forecasting provides essential information to empower grid operators and system designers in generating an optimal wind power plant, and to balance the power supply and demand. In this paper, we present an extensive review of wind forecasting methods and the artificial neural network (ANN) prolific in this regard. The instrument used to measure wind assimilation is analyzed and discussed, accurately, in studies that were published from May 1st, 2014 to May 1st, 2018. The results of the review demonstrate the increased application of ANN into wind power generation forecasting. Considering the component limitation of other systems, the trend of deploying the ANN and its hybrid systems are more attractive than other individual methods. The review further revealed that high forecasting accuracy could be achieved through proper handling and calibration of the wind-forecasting instrument and method

EFFECT OF WASTE POLYETHYLENE TEREPHTHALATE BOTTLE FIBERS ON THE MECHANICAL PROPERTIES OF RECYCLED CONCRETE

The use of beverage containers, most of which are made of polyethylene terephthalate bottles, results in several problems with regard to sustainability. The purpose of this study was to evaluate and contrast the impact on the mechanical characteristics of concrete caused by the incorporation of polyethylene terephthalate bottle fibres in varying amounts. These fibres were generated by cutting bottles into precise dimensions (width of 5 mm and length of 25 mm), and they were used in various concentrations such as 0,25 %; 0,5 % and 1,0 % by volume of concrete with different amounts of recycled aggregate. To verify the reliability of the outcomes of the experiment, a statistical analysis was performed. According to the results, the concrete that contained 0 % recycled coarse aggregate and varying amounts of plastic fibres had a greater degree of workability compared with concrete that had either 50 % or 100 % recycled coarse aggregate. The comprehensive test findings demonstrated that the addition of polyethylene terephthalate fibres decreased compressive and split tensile strength. The study concluded that certain parameters, such as plastic fibres, curing days, and recycled aggregate, interacted together in a synergistic manner to impact the compressive and splitting tensile strengths of the concrete, with proposed equations for their prediction

Visual Speaker Identification Using Lip and Body Movements

Speaker identification has been studied in many fields such as image processing, audio processing, artificial intelligence and speech recognition. Two of these areas are integrated together in order to identify the speaker. This research will focus on two main approaches which are lip movements and body movements. We will work on the two approaches to achieve the speaker identification. The expected outcome of this study will be to identify the speaker in different scenarios, if there is a single speaker or if there is multiple speakers in the video or if the speaker’s lips are not in view

Determination of Crop Coefficient of Hybrid Wheat under Arid Climate: A Pot Study

Climate change increases vulnerabilities for crop productivity in Pakistan. Water crises are increasing with an increase in temperature and change in precipitation patterns due to climate change which ultimately imposed a threat to the food security of the country. Water is indispensable for all plants to complete life cycle as the unavailability of water at critical growth stages drastically affects the development of the plant. The present pot study was conducted for the estimation of crop coefficient of hybrid wheat for irrigation scheduling at Muhammad Nawaz Shareef University of Agriculture, Multan during two growing seasons 2018-19 and 2019-20. In this experiment, three wheat varieties were used were Hybrid-1 (R26-3-1/DH-16), Hybrid-2(AR 7-5 / ZWB-14), and Galaxy-2013 as treatment. The soil moisture content was maintained between 50 to 100 % available water content (AWC) during both growing seasons. The crop coefficient (Kc) and actual evapotranspiration (Eta) were maximum in galaxy-13 and minimum in hybrid wheat. The grain yield for Hybrid-1, Hybrid-2, and galaxy-13 was 1, 1.5, and 0.6 g plant-1, respectively while the straw output was 4.8, 4.3, and 3 g plant-1, respectively. The harvest index for Hybrid-1, Hybrid-2, and galaxy-13 were 20, 34, and 20% respectively. The water use efficiency (WUE) for Hybrid-1, Hybrid-2, and galaxy-13 was 0.2. 0.3 and 0.1 g plant-1mm-1, respectively. The Hybrid-1 and Hybrid-2 produced more grain yield, straw yield, more spikes, and more grains per spikes and showed more water use efficiency with short plant height as compared to galaxy-13. The results of the study revealed that Hybrid-2 is more water-efficient with low water requirement and it was followed by Hybrid-1. The growing of Hybrid-2 will enhance the wheat yield to meet the food requirements of the increasing population under the climate change scenario with less water

Improving Growth and Yield of Sunflower with Integrated Use of Compost and PGPR (Variovorax Paradoxus) with Different Levels of N-Chemical Fertilizer

Plant growth-promoting rhizobacteria (PGPRs) stimulate plant growth through their ability, to increasing the root length and growth, by asymbiotic nitrogen fixation, by producing siderophores, solubilization of mineral phosphates and mineralization of other nutrients. Organic waste material of fruits and vegetables was collected and composted in a locally fabricated composting unit. A pot trial was conducted to study the effectiveness of compost and PGPR (Variovorax paradoxus) with recommended rate of PK and with different rates of N fertilizer i.e. 50 %, 75 % and 100 %, on growth and yield of sunflower. Results showed that the integrated use of 75 % N of recommended dose in combination with PGPR inoculation and compost caused a significant increase in grain yield and yield-contributing parameters compared with control. PGPR isolate Variovorax paradoxus in combination with 75 % N of recommended dose and compost gave maximum total achene’s yield 73 % more than control where recommended NPK was applied. Similarly, in case of Plant height, root length, head diameter, head weight, 100 – Achene’s weight and nitrogen content in straw were also increased by PGPR isolate Variovorax paradoxus in combination with 75 % N of the recommended dose and compost up to 11, 109, 27, 26, 17, and 54.0 % respectively over control

Dynamic Evaluation of Desiccant Dehumidification Evaporative Cooling Options for Greenhouse Air-Conditioning Application in Multan (Pakistan)

This study provides insights into the feasibility of a desiccant dehumidification-based Maisotsenko cycle evaporative cooling (M-DAC) system for greenhouse air-conditioning application. Conventional cooling techniques include direct evaporative cooling, refrigeration systems, and passive/active ventilation. which are commonly used in Pakistan; however, they are either not feasible due to their energy cost, or they cannot efficiently provide an optimum microclimate depending on the regions, the growing seasons, and the crop being cultivated. The M-DAC system was therefore proposed and evaluated as an alternative solution for air conditioning to achieve optimum levels of vapor pressure deficit (VPD) for greenhouse crop production. The objective of this study was to investigate the thermodynamic performance of the proposed system from the viewpoints of the temperature gradient, relative humidity level, VPD, and dehumidification gradient. Results showed that the standalone desiccant air-conditioning (DAC) system created maximum dehumidification gradient (i.e., 16.8 g/kg) and maximum temperature gradient (i.e., 8.4 °C) at 24.3 g/kg and 38.6 °C ambient air conditions, respectively. The DAC coupled with a heat exchanger (DAC+HX) created a temperature gradient nearly equal to ambient air conditions, which is not in the optimal range for greenhouse growing conditions. Analysis of the M-DAC system showed that a maximum air temperature gradient, i.e., 21.9 °C at 39.2 °C ambient air condition, can be achieved, and is considered optimal for most greenhouse crops. Results were validated with two microclimate models (OptDeg and Cft) by taking into account the optimality of VPD at different growth stages of tomato plants. This study suggests that the M-DAC system is a feasible method to be considered as an efficient solution for greenhouse air-conditioning under the climate conditions of Multan (Pakistan)

An Efficient and Simplified Model for Forecasting using SRM

Learning form continuous financial systems play a vital role in enterprise operations. One of the most sophisticated non-parametric supervised learning classifiers, SVM (Support Vector Machines), provides robust and accurate results, however it may require intense computation and other resources. The heart of SLT (Statistical Learning Theory), SRM (Structural Risk Minimization )Principle can also be used for model selection. In this paper, we focus on comparing the performance of model estimation using SRM with SVR (Support Vector Regression) for forecasting the retail sales of consumer products. The potential benefits of an accurate sales forecasting technique in businesses are immense. Retail sales forecasting is an integral part of strategic business planning in areas such as sales planning, marketing research, pricing, production planning and scheduling. Performance comparison of support vector regression with model selection using SRM shows comparable results to SVR but in a computationally efficient manner. This research targeted the real life data to conclude the results after investigating the computer generated datasets for different types of model buildin

Flood Frequency Analysis and Hydraulic Design of Bridge at Mashan on River Kunhar

Kunhar River hydrology and hydraulic design of a bridge on this river are being studied using HEC-Geo-RAS and Hydrologic Engineering Centers River Analysis System (HEC-RAS). The river flows in the northern part of Pakistan and is 170 km long. On both sides of the river, there are residential settlements. The river hydraulics is studied by using 30-metre remotely sensed shuttle radar topographic mission - digital elevation model (SRTM DEM) and Arc Map. 32 cross-sections are imported from Geographic Information System (GIS) to HEC-RAS. On historical peak flow results, the extreme value frequency distribution is applied, and a flood is determined for a 100-year return period, with a discharge estimated as 2223 cubic metres. Three steady flow profiles are adopted for HEC-RAS, the first is for the maximum historical peak data, the second is for the 100-year return period, and the third profile is for the latter 100-year period with a safety factor of 1.28. With remote sensing-based assessments, the proposed location for a bridge is determined and then verified with a field survey which was physically conducted. The maximum water height estimated in the river is about 4.26 m. This bridge will facilitate about 50 thousand population of Masahan and its surroundings. It will create a shortest link between Khyber Pakhtunkhwa and Azad Kashmir and thus will enhance tourism and trade activities