澄海莱芜人工鱼礁集鱼效果初步评价

2003和2007年分别对澄海莱芜人工鱼礁区进行了投礁前的本底调查和投礁后的跟踪调查。结果表明,投礁后礁区海域游泳生物的资源密度明显比投礁前高,增加了25．63倍;礁区海域各类资源种类均比投礁前丰富,总种数由投礁前的23种增加至41种,比投礁前增加了0．78倍,其中,蟹类种数增加最多,增加了1．75倍;在本底调查中没有出现的经济种类龙头鱼Harpodon nehereus和红星梭子蟹Portunus sanguinolentus在跟踪调查中已成为主要优势种;Shannon—Wienver多样性指数（H’）在礁区和对比区均比投礁前有所增加。表明鱼礁投放后,鱼礁区集鱼效果和群落结构明显改善,人工鱼礁建设取得了明显的生态效益和经济效益。     

Effects of landscape structure on nest predation in roadsides of a midwestern agroecosystem: a multiscale analysis

Nest predation is an important cause of mortality for many bird species, especially in grassland ecosystems where generalist predators have responded positively to human disturbance and landscape fragmentation. Our study evaluated the influence of the composition and configuration of the surrounding landscape on nest predation. Transects consisting of 10 artificial ground nests each were set up in 136 roadsides in six watersheds in south-central Iowa. Nest predation on individual roadside transects ranged from 0 to 100% and averaged 23%. The relationship of landscape structure within spatially-nested landscapes surrounding each roadside transect (within 200, 400, 800, 1200, and 1600 m of the transect line) to nest predation was evaluated by using multiple regression and canonical correlation analyses. The results of this multiscale landscape analysis demonstrated that predation on ground nests was affected by the surrounding landscape mosaic and that nest predators with different-sized home ranges and habitat affinities responded to landscapes in different ways. In general, wooded habitats were associated with greater nest predation, whereas herbaceous habitats (except alfalfa/pasture) either were associated with less nest predation or were not important. Different landscape variables were important at different spatial scales. Whereas some block-cover habitats such as woodland were important at all scales, others such as rowcrops and alfalfa/pasture were important at large scales. Some strip-cover habitats such as gravel roads and paved roads were important at small scales, but others such as wooded roadsides were important at all all scales. Most landscape metrics (e.g., mean patch size and edge density) were important at large scales. Our study demonstrated that the relationships between landscape structure and predator assemblages are complex, thus making efforts to enhance avian productivity in agricultural landscapes a difficult management goal.     

New Approaches to Modeling Methyl Jasmonate Effects on Pomegranate Quality during Postharvest Storage

Adaptive neuro fuzzy inference system (ANFIS) and genetic algorithm–artificial neural network (GA-ANN) models were used to predict the effect of methyl jasmonate (at three levels 0, 0.01, and 0.1 mM) and storage time (0, 14, 28, 42, 56, 70, and 84 days) on quality parameters and physiological changes of pomegranate fruits during storage. Methyl jasmonate reduced chilling injury and improved quality characteristics of pomegranates during postharvest storage. The GA-ANN and ANFIS were fed with two inputs of methyl jasmonate and storage time. The results showed that GA-ANN predictions agreed with experimental data and the GA-ANN with 14 neurons in one hidden layer can predict physiological changes and quality parameters of pomegranate (weight loss, pH, chilling injury index, ion leakage, ethylene, respiration, polyphenols, anthocyanins, and total antioxidant activity) with correlation coefficients equal to 0.87. The ANFIS model was trained by a hybrid method and agreement between experimental data and ANFIS predictions was significant (r = 0.90).     

考虑非线性摩擦模型的机器人动力学参数辨识

针对机器人动力学参数辨识的问题,提出了一种基于人工蜂群算法的辨识方法。考虑到关节摩擦特性,引入非线性摩擦模型,推导了机器人动力学模型的非线性形式。设计满足速度、加速度边界条件的五阶傅里叶级数作为激励轨迹来采集实验数据;利用人工蜂群算法,以蜂群为搜索单位,通过群体间的信息交流方式与优胜劣汰机制,对模型中的未知参数进行了辨识。最后,对得到的辨识模型进行了分析与验证,结果表明通过辨识得到关节预测力矩与测量力矩有较高的匹配度,所建立的非线性模型能够更好地描述机器人的动力学特性。     

小型无人直升机航向线性自抗扰控制

针对小型无人直升机航向系统存在内部不确定性和外部扰动大的问题,提出了一种基于线性自抗扰控制(LADRC)算法来实现航向通道高性能控制方法。首先,分析和推导了Trex-600型无人直升机的航向模型,并引入阵风模型模拟实际飞行环境。然后,根据LADRC的控制原理设计了基于二阶LADRC的航向控制系统,并利用人工蜂群算法对控制器参数进行了整定。最后,对所设计的控制策略进行了仿真分析与实验验证,实现了无人直升机航向通道的轨迹跟踪控制,并与常见的PID控制进行了比较。结果表明:设计的LADRC控制器鲁棒性好、响应时间快、控制精度高,能够使Trex-600型无人直升机的航向角快速、精确地跟踪参考轨迹。     

基于元胞自动机模型的土地利用情景模拟与驱动力分析

土地利用格局的形成过程比其最终形成的结果更为重要。本文以哈尔滨市双城区为例,利用不同时期的土地利用数据,在土地利用变化关键驱动因素分析的基础上,选取了对土地利用变化影响较大的距离变量、邻近土地利用类型数量、单元自然属性、社会经济因素等4方面14个驱动力因子,建立了基于元胞自动机(CA)与人工神经网络(ANN)相结合的土地利用空间格局模拟模型。在此基础上,对研究区自然禀赋、社会经济快速发展、基本农田保护及土地利用规划等不同情景驱动机制下的土地利用空间格局进行了时空模拟,以此解析土地利用变化过程与驱动力因素的响应关系。模拟结果显示：自然禀赋情景下,各地类变化趋势与现在保持一致;在社会经济快速发展情景下,建设用地面积增加明显,主要由旱地和其他用地转入;在基本农田保护情景下,耕地面积比较稳定,各地类变化趋势较为缓和;在土地利用规划情景下,各地类变化较为合理,兼顾耕地保护和经济发展。研究结果显示,该方法对哈尔滨市双城区土地利用格局变化的驱动机制具有较好的解释作用。     

人工老化对小麦种子活力及醇溶蛋白组成的影响

为揭示种子活力与醇溶蛋白组成变化的关系,以小麦品种百农矮抗58、周麦18、新麦208、郑麦9023和杂交小麦(BNS/05525)为材料,高温(43±1)℃、高湿(95％相对湿度)老化处理0,4,6,9,12,15d和20 d,对老化处理种子的活力及醇溶蛋白组成进行了分析.结果表明,随着老化时间的延长,小麦种子的发芽势、发芽率、发芽指数和活力指数逐渐降低,老化20 d的小麦种子发芽势、发芽率、发芽指数和活力指数均降为0,种子活力丧失.在同一老化程度下,杂交小麦种子的发芽势、发芽指数、活力指数均高于百农矮抗58、周麦18、新麦208、郑麦9023,说明杂交小麦的抗老化能力较强;电导率在种子老化的0～12 d内变化较小,种子老化到15d时电导率迅速升高;5个小麦品种种子老化20 d后,发芽率从100％下降到0,醇溶蛋白的表达均出现了带型的变化,ω区醇溶蛋白出现了谱带的丢失、新蛋白的增加及蛋白表达量的上升和下降.种子活力丧失与蛋白的丢失、新谱带的产生都是在同一时间(种子老化20 d),说明种子活力的丧失与ω区域醇溶蛋白的消失和新增加的蛋白质有关;种子老化程度的加剧,导致了某些存活能力差的基因型消失,消失的基因可能与种子活力的表达相关.     

基于人工智能的农用拖拉机发动机故障快速诊断研究

为了达到拖拉机发动机不解体故障诊断的目的,提高诊断效率,利用发动机缸盖的振动信号的采集原理,提出了一种基于神经网络的人工智能故障检测方法,并构建了拖拉机发动机振动信号采集系统。基于人工智能的拖拉机发动机故障诊断系统,综合运用信号采集技术、信号处理技术、数据库技术、神经网络技术和人工智能专家系统,实现了和数据库及具有强大信号分析的处理功能,提高了系统的诊断实时性和诊断精度。最后,采用田间试验方法,对拖拉机故障快速诊断系统进行了试验验证。试验结果表明:采用人工智能诊断方法不仅可以有效提高系统的准确率,而且诊断系统的响应更加迅速,并且曝晒、震动、灰尘等恶劣的现场环境中仍能保持正常工作的稳定性。     

三江平原主栽大豆品种对大豆根腐病尖孢镰孢菌的抗性分析

明确三江平原地区主栽大豆品种对主要大豆根腐病致病菌尖孢镰孢菌的抗性。收集了该地区主栽大豆品种13 个,对其同时进行盆栽接种和大田接种尖孢镰孢菌的抗性分析试验,大田接种试验设不接种对照。‘垦丰16’和‘合丰55’的抗性最好,盆栽试验中均表现为抗病,平均病情指数分别为15.33%和20.67%,大田接种试验中表现为抗病,病情指数分别为25.55%和22.89%,与未接种对照相比,减产率最低,分别为3.55%和3.77%,差异达到显著水平。‘垦丰16’和‘合丰55’是适宜三江平原地区种植的抗尖孢镰孢菌根腐病的抗病品种。     

苹果病害智能诊断方法研究与设计

针对传统苹果专家病害诊断系统自学习能力差、准确率低的不足,研究并设计了人工神经网络的苹果病害诊断方法.采用动态编码对苹果病害模糊知识进行量化,构建BP网络诊断模型进行诊断;采用Java语言开发基于Web的病害动态诊断平台,用白水苹果病害样本进行了实验.该方法对20种苹果病害的诊断具有较好的效果,测试准确率达到85.4%.在获得必要领域知识的前提下,用神经网络进行苹果病害诊断准确率高,系统设计灵活,基于Web的诊断平台便于推广和使用.