Abstract  

  In this work, two algorithms of Metaheuristic algorithms were hybridized. The first is Invasive Weed Optimization algorithm (IWO) it is a numerical stochastic optimization algorithm and the second is Whale Optimization Algorithm (WOA) it is an algorithm based on the intelligence of swarms and community intelligence. Invasive Weed Optimization Algorithm (IWO) is an algorithm inspired by nature and specifically from the colonizing weeds behavior of weeds, first proposed in 2006 by Mehrabian and Lucas. Due to their strength and adaptability, weeds pose a serious threat to cultivated plants, making them a threat to the cultivation process. The behavior of these weeds has been simulated and used in Invas

This study investigated the feasibility of anaerobic co-digestion of giant reed (GR) inoculated with waste manure as a co-substrate for biogas production. The performance of co-digestion was evaluated in 4 anaerobic digesters operated in batch mode at different conditions. The effects of alkali pretreatment with NaOH (4% w/v) solution, inoculum type, and thermal condition were studied. The results demonstrated that the alkali-pretreatment of GR enhanced the biogas generation by about 15% at mesophilic conditions. Thermophilic conditions enhanced the biogas recovery from both alkali-free and alkali pretreated GR by 15% and 127%, respectively. The kinetic study of the co-digestion process of GR for biogas recovery suggeste

<p>In combinatorial testing development, the fabrication of covering arrays is the key challenge by the multiple aspects that influence it. A wide range of combinatorial problems can be solved using metaheuristic and greedy techniques. Combining the greedy technique utilizing a metaheuristic search technique like hill climbing (HC), can produce feasible results for combinatorial tests. Methods based on metaheuristics are used to deal with tuples that may be left after redundancy using greedy strategies; then the result utilization is assured to be near-optimal using a metaheuristic algorithm. As a result, the use of both greedy and HC algorithms in a single test generation system is a good candidate if constructed correctly. T

Massive multiple-input multiple-output (massive-MIMO) is a promising technology for next generation wireless communications systems due to its capability to increase the data rate and meet the enormous ongoing data traffic explosion. However, in non-reciprocal channels, such as those encountered in frequency division duplex (FDD) systems, channel state information (CSI) estimation using downlink (DL) training sequence is to date very challenging issue, especially when the channel exhibits a shorter coherence time. In particular, the availability of sufficiently accurate CSI at the base transceiver station (BTS) allows an efficient precoding design in the DL transmission to be achieved, and thus, reliable communication systems can be obtaine

Electrical distribution system loads are permanently not fixed and alter in value and nature with time. Therefore, accurate consumer load data and models are required for performing system planning, system operation, and analysis studies. Moreover, realistic consumer load data are vital for load management, services, and billing purposes. In this work, a realistic aggregate electric load model is developed and proposed for a sample operative substation in Baghdad distribution network. The model involves aggregation of hundreds of thousands of individual components devices such as motors, appliances, and lighting fixtures. Sana’a substation in Al-kadhimiya area supplies mainly residential grade loads. Measurement-based

Many consumers of electric power have excesses in their electric power consumptions that exceed the permissible limit by the electrical power distribution stations, and then we proposed a validation approach that works intelligently by applying machine learning (ML) technology to teach electrical consumers how to properly consume without wasting energy expended. The validation approach is one of a large combination of intelligent processes related to energy consumption which is called the efficient energy consumption management (EECM) approaches, and it connected with the internet of things (IoT) technology to be linked to Google Firebase Cloud where a utility center used to check whether the consumption of the efficient energy is s

The Ratawi Oil Field (ROF) is one of Iraq's most important oil fields because of its significant economic oil reserves. The major oil reserves of ROF are in the Mishrif Formation. The main objective of this paper is to assess the petrophysical properties, lithology identification, and hydrocarbon potential of the Mishrif Formation using interpreting data from five open-hole logs of wells RT-2, RT-4, RT-5, RT-6, and RT-42. Understanding reservoir properties allows for a more accurate assessment of recoverable oil reserves. The rock type (limestone) and permeability variations help tailor oil extraction methods, extraction methods and improving recovery techniques. The petrophysical properties were calculated using Interactive Petroph