Strategic Renewable Energy Resource Selection Using a Fuzzy Decision-Making Method

Renewable energy is created by renewable natural resources such as geothermal heat,sunlight,tides,rain,and wind.Energy resources are vital for all countries in terms of their economies and politics.As a result,selecting the optimal option for any country is critical in terms of energy investments.Every country is nowadays planning to increase the share of renewable energy in their universal energy sources as a result of global warming.In the present work,the authors suggest fuzzy multi-characteristic decision-making approaches for renew-able energy source selection,and fuzzy set theory is a valuable methodology for dealing with uncertainty in the presence of incomplete or ambiguous data.This study employed a hybrid method for order of preference by resemblance to an ideal solution based on fuzzy analytical network process-technique,which agrees with professional assessment scores to be linguistic phrases,fuzzy numbers,or crisp numbers.The hybrid methodology is based on fuzzy set ideologies,which calculate alternatives in accordance with professional functional requirements using objective or subjective characteristics.The best-suited renewable energy alternative is discovered using the approach presented.

Progress in research on the exploration and evaluation of deep geothermal resources in the Fujian-Guangdong-Hainan region,China

Deep geothermal resources in the Fujian-Guangdong-Hainan region,China,offer significant potential for sustainable energy.The diverse igneous rock formations along the southeast coast present intricate geological challenges that impede exploration and evaluation efforts.In this study,we address critical concerns related to the Fujian-Guangdong-Hainan region's deep geothermal resources,encompassing heat source composition,formation conditions,strategic favorable areas,and exploration directions.Our methods involve the analysis of regional geothermal reservoirs and cap rocks.Major findings include:the primary heat sources in the Fujian-Guangdong-Hainan region consist of the radioactive heat generation from granites in the crust,heat conduction in the mantle,and,in specific areas like Yangjiang and Shantou,melts within the middle and lower crust;the deep,high-temperature geothermal resources in the region predominantly reside in basins'depressed areas.These areas are characterized by the confluence of triple heat sources:heat from the Earth's crust,mantle,and other supplementary sources;our analysis led to the identification of three strategic areas favorable for deep geothermal resources in the Fujian-Guangdong-Hainan region.These are the Beibu Gulf Basin's continental area,the Yuezhong Depression,and the Fuzhou-Zhangzhou area.

Mode Selection and Resource Allocation for Deviceto-Device Communications in 5G Cellular Networks

To meet the increasing demand of wireless broadband applications in future 5G cellular networks, Device-to-Device(D2D) communications serve as a candidate paradigm to improve spectrum efficiency. Considering the challenges after D2 D transmission is introduced for future cellular networks, this paper deals with mode selection and resource allocation issues related with D2 D communications. First, we propose a mode selection scheme which aims at guaranteeing the transmission of cellular users and also considering the potential interference. We analyze the condition under which D2 D underlay mode should be used. Second, we answer the question of "how to effectively reuse cellular resource once underlaying mode is adopted". We further present a resource allocation scheme that focuses on minimizing overall interference as well as a power control method to improve the performance of D2 D systems. Simulation results demonstrate that system parameters greatly affect the switching condition of mode selection and probability of choosing underlay mode. Furthermore, for D2 D underlaying scenario, the proposed resource allocation algorithm guarantees the transmission of cellular users with consideration of transmission requirements of D2 D users. Hence, the proposed scheme can achieve better user experience.

Cultivar selection can increase yield potential and resource use efficiency of spring maize to adapt to climate change in Northeast China

Northeast China (NEC) is one of the major maize production areas in China.Agro-climatic resources have obviously changed,which will seriously affect crop growth and development in this region.It is important to investigate the contribution of climate change adaptation measures to the yield and resource use efficiency to improve our understanding of how we can effectively ensure high yield and high efficiency in the future.In this study,we divided the study area into five accumulated temperature zones (ATZs) based on growing degree days (GDD).Based on the meteorological data,maize data (from agrometeorological stations) and the validated APSIM-Maize Model,we first investigated the spatial distributions and temporal trends of maize potential yield of actual planted cultivars,and revealed the radiation use efficiency (RUE) and heat resource use efficiency (HUE) from 1981 to 2017.Then according to the potential growing seasons and actual growing seasons,we identified the utilization percentages of radiation (P_R) resource and heat resource (P_H) for each ATZ under potential production from 1981 to 2017.Finally,we quantified the contributions of cultivar changings to yield,P_R and P_H of maize.The results showed that during the past 37 years,the estimated mean potential yield of actual planted cultivars was 13 649 kg ha^(–1),ranged from 11 205 to 15 257 kg ha^(–1),and increased by 140 kg ha^(–1) per decade.For potential production,the mean values of RUE and HUE for the actual planted maize cultivars were 1.22 g MJ^(–1) and 8.58 kg (℃ d)^(–1) ha^(–1).RUE showed an increasing tendency,while HUE showed a decreasing tendency.The lengths of the potential growing season and actual growing season were 158 and 123 d,and increased by 2 and 1 d per decade.P_R and P_H under potential production were 82 and 86%,respectively and showed a decreasing tendency during the past 37 years.This indicates that actual planted cultivars failed to make full use of climate resources.However,results from the adaptation assessments indicate that,adoption of cultivars with growing season increased by 2–11 d among ATZs caused increase in yield,P_R and P_H of 0.6–1.7%,1.1–7.6% and 1.5–8.9%,respectively.Therefore,introduction of cultivars with longer growing season can effectively increase the radiation and heat utilization percentages and potential yield.

Energy Efficient Constrained Shortest Path First-Based Joint Resource Allocation and Route Selection for Multi-Hop CRNs

Cognitive radio networks(CRNs) are expected to improve spectrum utilization efficiently by allowing secondary users(SUs) to opportunistically access the licensed spectrum of primary users(PUs).In CRNs,source and destination SUs may achieve information interaction in an ad hoc manner.In the case that no direct transmission link between the SU transmission pairs is available,multi-hop relay SUs can be applied to forward information for the source and destination SUs,resulting in multi-hop CRNs.In this paper,we consider a multi-hop CRN consisting of multiple PUs,SU transmission pairs and relay SUs.Stressing the importance of transmission hops and the tradeoff between data rate and power consumption,we propose an energy efficient constrained shortest path first(CSPF)-based joint resource allocation and route selection algorithm,which consists of two sub-algorithms,i.e.,CSPF-based route selection sub-algorithm and energy efficient resource allocation sub-algorithm.More specifically,we first apply CSPF-based route selection sub-algorithm to obtain the shortest candidate routes(SCRs) between the SU pair under the transmission constraints.Then,an energy efficient resource allocation problem of the SCRs is formulated and solved by applying iterative algorithm and Lagrange dual method.Simu-lation results demonstrate the effectiveness of the proposed algorithm.

Optimal joint relay selection and resource allocation with QoS constraints in multiuser OFDM-based cellular networks

This paper investigates the relay selection and resource allocation problem in multiuser orthogonal frequency division multiplexing （OFDM） based cooperative cellular networks, in which user nodes could relay information for each other using the decode-and-forward （DF） protocol to achieve spatial diversity gain. Specifically, the paper proposes an optimal joint relay selection and resource allocation （0RSRA） algorithm whose objective is to maximize system total achievable data rate with the constraints of each user＇ s individual quality of service （QoS） requirement and transmission power. Due to being a mixed binary integer programming （MBIP） problem, a novel two-level Lagrangian dual-primal decomposition and subgradient projection approach is proposed to not only select the appropriate cooperative relay nodes, but also allocate subcarries and power optimally. Simulation re- suits demonstrate that our proposed scheme can efficiently enhance overall system data rate and guarantee each user＇ s QoS requirement. Meanwhile, the fairness among users can be improved dramatically.

Evaluation and selection of the ship collaborative design resources based on AHP and genetic and simulated annealing algorithm

The characteristics of the design resources in the ship collaborative design is described and the hierarchical model for the evaluation of the design resources is established. The comprehensive evaluation of the co-designers for the collaborative design resources has been done from different aspects using Analytic Hierarchy Process （AHP） ,and according to the evaluation results,the candidates are determined. Meanwhile,based on the principle of minimum cost,and starting from the relations between the design tasks and the corresponding co-designers,the optimizing selection model of the collaborators is established and one novel genetic combined with simulated annealing algorithm is proposed to realize the optimization. It overcomes the defects of the genetic algorithm which may lead to the premature convergenee and local optimization if used individually. Through the application of this method in the ship collaborative design system,it proves the feasibility and provides a quantitative method for the optimizing selection of the design resources.

Efficient Task Scheduling for Many Task Computing with Resource Attribute Selection

Many Task Computing(MTC)is a new class of computing paradigm in which the aggregate number of tasks,quantity of computing,and volumes of data may be extremely large.With the advent of Cloud computing and big data era,scheduling and executing large-scale computing tasks efficiently and allocating resources to tasks reasonably are becoming a quite challenging problem.To improve both task execution and resource utilization efficiency,we present a task scheduling algorithm with resource attribute selection,which can select the optimal node to execute a task according to its resource requirements and the fitness between the resource node and the task.Experiment results show that there is significant improvement in execution throughput and resource utilization compared with the other three algorithms and four scheduling frameworks.In the scheduling algorithm comparison,the throughput is 77%higher than Min-Min algorithm and the resource utilization can reach 91%.In the scheduling framework comparison,the throughput(with work-stealing)is at least 30%higher than the other frameworks and the resource utilization reaches 94%.The scheduling algorithm can make a good model for practical MTC applications.

The Core Mechanism of Natural Selection: How the Natural Cycle of Potassium Resources Affects the Biological Evolution and the Change of Human Society

Darwin’s theory of evolution believes that biological evolution is a process of natural selection. This theory has been supported by much evidence, but the internal biological mechanism is not clear. Here, I elaborate on the cycle of potassium resources on the earth and the biological utilization and efficiency, which may be the core mechanism of natural selection and affect the evolution of organisms and the development of human society.

A Joint User Selection and Resources Optimization Scheduling Algorithm for CoMP

Coordinated Multi-point (CoMP) transmission technology is one of the key techniques in LTE-Advanced, Which can share the channel and data information in multiple cells, and optimize the whole system performance. In order to optimize the average sector throughput and improve the fairness of resource scheduling, a scheduling algorithm based on the resource is mainly investigated. In this algorithm, users in the network are classified firstly and then we combine the fixed resources division and flexible scheduling. System level simulation platform is set up to validate the algorithm and the results turn out that the average throughput is better compared with the traditional scheme.

Tabu Search Solution for Resource Confidence Considered Partner Selection Problem in Cross-Enterprise Project

Cross-enterprise project is the main implementation form in multi enterprises collaborative production environment. Minimizing the risk of failure and tardiness caused by the uncertainty of partner’s resources in partner selection is the key problem to ensure success in Cross-enterprise project. In this paper, considering the factors and constraints of sub-project processing times, precedence of sub-project and project due date, especially the resource confidence, a 0-1 integer programming model was presented with the objective to minimize the risk of failure and the tardiness of the project. A project scheduling algorithm was designed to search and evaluate selection solutions, and the project scheduling algorithm was embedded into a Tabu search algorithm to solve the model. Simulation experiments and comparisons with other algorithms showed that the proposed approach was possible to find the optimal solution with a faster speed and higher probability.

Joint User Selection and Resource Allocation for Fast Federated Edge Learning

By periodically aggregating local learning updates from edge users, federated edge learning (FEEL) is envisioned as a promising means to reap the benefit of local rich da?ta and protect users'privacy. However, the scarce wireless communication resource greatly limits the number of participated users and is regarded as the main bottleneck which hin?ders the development of FEEL. To tackle this issue, we propose a user selection policy based on data importance for FEEL system. In order to quantify the data importance of each user, we first analyze the relationship between the loss decay and the squared norm of gradi?ent. Then, we formulate a combinatorial optimization problem to maximize the learning effi?ciency by jointly considering user selection and communication resource allocation. By problem transformation and relaxation, the optimal user selection policy and resource alloca?tion are derived, and a polynomial-time optimal algorithm is developed. Finally, we deploy two commonly used deep neural network (DNN) models for simulation. The results validate that our proposed algorithm has strong generalization ability and can attain higher learning efficiency compared with other traditional algorithms.

Recruitment and selection of Human Resources --Alibaba business, for example

Human resources is one of the important aspects of an enterprise survival and development.The competition of an enterprise is ultimately a competition of human resources. It is no exaggeration to say that human resources are the core strength of an enterprise survival and development. If there is no good human resources, then the business may be just a shell, no pillars and core development, then it can not go on long-term development. With the development of international, multinational companies continue to grow, the demand for human resources is placed in a prominent position. Human resources management including human resource planning, human resources recruitment and selection, training and development of human resources, human resources performance management, compensation of human resources, labor relations. This paper studies the recruitment and selection of human resources, and Alibaba, for example, described in detail the meaning of the recruitment and selection methods and the role in order to provide a theoretical reference for future research and business recruitment.

A Multi-Agent Resource Selection Model in Manufacturing Grid Environment

A group of agents are intimately cooperated to set the assessment indices, establish the weight of each index in overall result of evaluation, collect the experts＇ scores given to each available resource, and the manufacturing resource whose overall assessment value is highest is taken as the optimal choice. Architecture of the proposed system is outlined and an example is offered to show the process of accomplishing the assessment.

A preliminary study on criteria weights for a library's digital resource selection:From the viewpoints of both users and librarians

Through investigating both users' and librarians' perceptions of the relative importance of the major criteria governing the selection of digital resources, we attempted to develop a criterion weight framework for a library's selection of digital resources, which can meet both the users' requirements and the library's goal of developing digital collections. The respective weight of each specific criterion is decided through the Analytic Hierarchy Process(AHP) Method. The findings of this study indicate that, when assigning weights to the selection criteria, it is important to consult the opinions of a wide crosssection of people, especially the views of different users. As a result, the digital resource selection system characterized by the criteria weights can reflect more comprehensively the users' requirements, and meanwhile it enables librarians' more rational selection of digital resources.

Research on Fuzzy Decision of Resources Selection in Job-sh op Scheduling for a One-of-a-Kind and Order-Oriented Production System

In a one-of-a-kind and order-orient ed production corporation, job shop scheduling plays an important role in the prod uction planning system and production process control. Since resource selection in job shop scheduling directly influences the qualities and due dates of produc ts and production cost, it is indispensable to take resource selection into acco unt during job shop scheduling. By analyzing the relative characteristics of res ources, an approach of fuzzy decision is proposed for resource selection. Finall y, issues in the application of the approach are discussed.

Threshold Selection and Resource Allocation for Quantized Identification

This paper is concerned with the optimal threshold selection and resource allocation problems of quantized identification, whose aims are improving identification efficiency under limited resources. Firstly, the first-order asymptotically optimal quantized identification theory is extended to the weak persistent excitation condition. Secondly, the characteristics of time and space complexities are established based on the Cramér-Rao lower bound of quantized systems. On these basis, the optimal selection methods of fixed thresholds and adaptive thresholds are established under aperiodic signals, which answer how to achieve the best efficiency of quantized identification under the same time and space complexity. In addition, based on the principle of maximizing the identification efficiency under a given resource, the optimal resource allocation methods of quantized identification are given for the cases of fixed thresholds and adaptive thresholds, respectively, which show how to balance time and space complexity to realize the best identification efficiency of quantized identification.

Make Leapfrogging Development By Concentrating Resource On Selected Targets

The Chinese Academy of Sci-ences (CAS) has begun introducingthe trial implementation of theKnowledge Innovation Program(KIP)in an all-round manner just as,at the beginning of the new century,the state is about to implement itsTenth Five-Year Plan for thecountry’s ongoing economic andsocial development. This will

Information System for Ocean Wave Resources and Its Application to Wave Power Utilization

An information system for ocean wave resources and its application to wave power utilization are introduced. It can manage, analyze and process the data in the monthly report of ocean wave observation records of the State Ocean Administration, and can provide various kinds of curves and numerical characters of statistics. This system has been put into utility in Guangzhou Institute of Energy Conversion (GIEC), the Chinese Academy of Sciences since 1996. An application example is given of the investigation and analysis on ocean wave resource of the Nan Ao Island, Guangdong Province, where a 100 kW onshore OWC (oscillating water column) wave power station will be built. The wave power distribution is obtained in different wave directions for different wave periods. It is found that 70 percent of the wave power comes from the direction of ENE, and more than 95 percent of the wave power is related with direction E. The average wave power density is about 3 kW/m, and more than 80 percent of the wave power is distributed in the wave periods of 4 second to 5 second. Based on the analysis of wave resources, a site on the east coast of the island and a design width of 20 m for the 100 kW station are suggested.

Downlink CoMP Resource Allocation Based on Limited Backhaul Capacity

Coordinated Multi-Point(CoMP) transmission is put forward in the Long Term Evolution-Advanced(LTE-A) system to improve both average and cell-edge throughput. In this paper, downlink CoMP(DL-CoMP) resource allocation scheme based on limited backhaul capacity is designed to take a tradeoff between system throughput and fairness. Resource allocation of proportional fairness based on querying table is proposed. It updates RB allocation matrix when center cell has completed resource allocation and delivers the matrix to adjacent cells for their own RB allocation. Furthermore, Water-Filling algorithm based on adaptive water level(AWF) is used for power allocation to boost system fairness. In this paper, performance of downlink CoMP based on limited backhaul capacity and single-point transmission is contrasted, and results indicate that CoMP dramatically enhances system throughput and spectral efficiency. Moreover, AWF power allocation scheme obtains higher system fairness than conventional Water-Filling(WF) algorithm, although it gets slightly lower system throughput. Finally, this paper discussed that the system performance is partially affected by the percentage of CoMP resource.